(15 intermediate revisions by the same user not shown)
Line 1: Line 1:
 
<!-- metadata commented in wiki content
 
<!-- metadata commented in wiki content
−
 
 
−
             
 
−
<div class="center" style="width: auto; margin-left: auto; margin-right: auto;">
 
−
<big>'''Information release right of scientific research institutions in health emergencies: Taking China as the research object'''</big></div>
 
−
               
 
−
<div class="center" style="width: auto; margin-left: auto; margin-right: auto;">
 
−
Shuai Li<sup>a</sup>''<sup>*</sup>''</div>
 
−
 
 
−
''<sup>a </sup>Law School, Beijing Foreign Studies University, Beijing, 100089, People’s Republic of China''
 
−
         
 
−
<span id='OLE_LINK28'></span>''<sup>*</sup>Corresponding address: [mailto:Norbertlau2019@163.com Norbertlau2019@163.com]''
 
−
-->==Abstract==
 
−
The integration of autonomous robotic systems is pivotal for advancing agricultural mechanization. A critical challenge impeding their widespread adoption is the achievement of reliable, self-sufficient navigation, particularly in environments where conventional positioning systems are compromised. While Global Navigation Satellite Systems (GNSS), often fused with auxiliary sensors, represent a primary solution for outdoor robot guidance, their susceptibility to signal occlusion necessitates alternative, stable methodologies for consistent operation. Addressing this limitation, this paper presents a novel, model-based navigation algorithm engineered specifically for orchard robots operating under prolonged GNSS denial. The core methodology leverages a deterministic kinematic model, deliberately neglecting higher-order dynamic effects justified by the inherently low operational speeds mandated in precision agricultural settings. This model directly processes commanded trajectory coordinates and real-time vehicle state estimates derived solely from incremental wheel encoders and a steering angle sensor. Within the MATLAB/Simulink environment, this transformation is implemented to generate precise longitudinal velocity and angular steering rate commands necessary for path tracking. Empirical validation was conducted through rigorous simulation and field trials employing a non-holonomic mobile robot platform in representative outdoor conditions. Performance evaluation confirmed the robot’s capability for satisfactory autonomous navigation. Quantitatively, the normalized root mean square error (NRMSE) for lateral path deviation during turning maneuvers ranged between 0.2 and 0.4, while straight-line travel exhibited minimal steering offset, typically within ±0.05 degrees. Furthermore, the correlation coefficient between the model’s predicted steering output and the actual commanded input consistently approached 0.99. Collectively, the results demonstrate that the proposed sensor-minimized, model-driven approach provides a viable and realistic foundation for achieving resilient vehicle navigation in structurally complex agricultural domains where GNSS reliability cannot be assured.       
 
  
−
'''Keywords''': Autonomous Navigation; Agricultural Robotics; GNSS-Denied Environments; Kinematic Modeling; Path Tracking Control
 
  
−
==1. Introduction==
+
<div class="center" style="width: auto; margin-left: auto; margin-right: auto;">
 +
<big>'''Quantum dynamics of dissipative Chern insulator'''</big></div>
  
−
The deployment of self-governing robotic platforms within agriculture has accelerated, driven by the need for novel vehicle solutions that elevate farm output, operational efficiency, and the capacity to execute diverse tasks within inherently variable agricultural settings. This trend offers a promising mitigation strategy for the growing scarcity of agricultural labor. Fundamental to the realization of such autonomous mobile systems is the capability for self-directed navigation. While the conceptual foundation for agricultural robotics was established as early as the mid-1980s [1], practical implementation has surged significantly in recent times. This acceleration is largely attributable to concurrent breakthroughs in computational capabilities, sensor technologies [2], and the advent of powerful, affordable processors. Progress in electronics and the commercialization of cost-effective sensors have rendered the development of economically viable robotic platforms for farm environments increasingly feasible. Nevertheless, the aspiration for fully autonomous robotic or vehicular movement remains partially unrealized within contemporary robotics, constrained by persistent technical hurdles. Outdoor navigation for agricultural robots presents particular difficulties, stemming from the challenge of obtaining precise environmental perception amidst fluctuating weather patterns, diverse terrain, and dynamic vegetation. Consequently, developing robust sensing and control strategies capable of accommodating these environmental characteristics is paramount. Supporting this, research by Bac et al. specifically investigated the detrimental impact of environmental variability on the operational efficacy of a harvesting robot [3]. Achieving a precise interpretation of environmental features and deploying resilient technologies for navigation and environmental detection under demanding conditions is crucial for striking an optimal balance between system cost and technological sophistication [4].
+
<div id="OLE_LINK26" class="center" style="width: auto; margin-left: auto; margin-right: auto;">
 +
Jilian Zhonga<sup> *</sup>, Xiaoyue Li<sup>a</sup></div>
  
−
Affordability is a critical consideration in agricultural technology development, given the primary end-users are farmers operating within constrained financial frameworks compared to other vehicle markets. System complexity inherently drives cost escalation, making the specific operational environment a vital factor in design philosophy. Orchards, characterized by their semi-structured spatial organization and defined biological architecture, present a highly conducive environment for the initial large-scale adoption of robotics and automation in farming [5]. This suitability is further amplified by a pressing concern: the diminishing availability of skilled seasonal labor poses a substantial risk to orchard sustainability, thereby establishing orchard automation as a critical priority [5].
+
''<sup>a</sup> Department of Physics, Jiangsu University, Zhenjiang 212013, People’s Republic of China''
  
−
Ongoing research and development efforts signal positive growth indicators for the agricultural robotics sector and the vital transition of these technologies from laboratory prototypes to practical field deployment, irrespective of current manufacturing volumes. Indeed, the pace of innovation in autonomous navigation specifically within agricultural robotics parallels trends observed in the broader automotive market, though the absolute scale of development may currently differ.
+
<span id='OLE_LINK28'></span>''<sup>*</sup>Corresponding address: [mailto:zhongjilian0505@163.com zhongjilian0505@163.com]''
 +
-->==Abstract==
 +
This research is aimed at Laser processing of micro holes there are recast layer and microcracks, analyzed the laser processing of recast layer formation mechanism and surface geometry features not, and for the laser processing of the formation of the recast layer in the process of analog simulation, for electrochemical finishing processing to remove the recast layer to provide a theoretical basis. The laser-electrolysis asynchronous composite processing experimental system was developed, and the electrolytic removal of recast layer on the wall of laser perforated holes and the process research of aperture trimming were carried out, which mainly analyzed the effects of electrolysis voltage, electrolyte and pulse electrolysis parameters on the rate of electrolysis and the effect of the removal of the recast layer. The cathode lifting method is also proposed to lift the tool cathode for orifice shaping after effective removal of the recast layer. The experimental results show that: when the current density is greater than 10.09 A/cm<sup>2</sup>, the electrolysis rate is proportional to the voltage; when the constant voltage electrolysis, the mixed solution of NaNO<sub>3</sub> and NaCl enhances the effect of the recast layer removal significantly, and relative to the single solution with the same electrical conductivity, the value of the change in the surface roughness of the workpiece before and after the finishing process is enhanced more significantly, and there is no significant difference in the processing efficiency; the low-frequency wide pulse and high-frequency narrow pulse in the pulse electrolysis processing is favorable for the removal of recast layer. Pulse, high-frequency narrow pulse is conducive to the improvement of electrolysis rate, and the frequency of 1 kHz, the duty cycle of 40% to 60% of the electrolysis rate is the largest; at the same time, the use of cathodic enhancement method of aperture trimming processing, the use of the truncation effect, through the appropriate electrolytic processing parameters, to achieve the complete removal of the laser hole hole wall recast layer at the same time to complete the aperture trimming processing, to meet the demand for the use of performance of the small holes to further enhance the processing efficiency and small holes, and to improve the processing efficiency of the laser hole. Enhance the processing efficiency and functionality of small holes.
  
−
Accurate localization constitutes a fundamental pillar for autonomous navigation in mobile robots, demanding sophisticated sensor integration and algorithmic processing. It remains a highly active area demanding continued advancement. Wang et al. explored the utilization of machine vision for robotic positioning and pathfinding [6]. Blok et al. demonstrated a combined Particle Filter and Kalman Filter approach for probabilistic localization, employing a 2D LIDAR scanner to enable in-row navigation for orchard robots [7]. Their empirical findings indicated superior performance of the Particle Filter model over the Kalman Filter in this specific context. The critical influence of the environment on localization efficacy is well-recognized; Schwarting et al. detailed the principal localization challenges encountered by terrestrial robots operating in diverse settings [8]. They offered a comprehensive analysis of existing methodologies tackling these challenges, their inherent limitations, and prospective future directions. Bechar and Vigneault provided a parallel overview of design, development, and operational considerations for agricultural robots, including their constraints, emphasizing the necessity for sensor fusion to achieve adequate localization and environmental awareness, alongside the development of adaptive path planning and navigation algorithms for variable conditions [9]. Contemporary research frequently focuses on enhancing navigation reliability through the fusion of Global Positioning System (GPS) data with complementary sensor modalities. For instance, Winterhalter et al. proposed an approach combining GNSS-referenced maps with GNSS signals for in-field localization and autonomous traversal along crop rows [10]. Thomasson et al. documented progress in automatic guidance and steering control, highlighting commercially available systems primarily reliant on Global Navigation Satellite Systems (GNSS) [11]. However, these commercial solutions are predominantly tailored for tractors and often necessitate human intervention when encountering unexpected field or navigation anomalies. Alternative configurations include the use of dual RTK-GPS receivers for navigating 4-wheel-steering agricultural rovers, or localization relying on laser scanners combined with wheel and steering encoders, albeit without integrated obstacle avoidance [12,13]. Zaidner and Shapiro presented a model-based state estimation approach for a vineyard robot utilizing sensor fusion. Recognizing the complexity of real-world testing [14], Linz et al. developed a 3D simulation environment using Gazebo for preliminary virtual validation of robotic navigation algorithms employing image-based sensors, laser scanners, and GPS, prior to outdoor deployment [15].
+
'''Keywords''': Laser processing, recast layer simulation, electrochemical finishing, cathodic lift   
 +
==1. Introduction==
 +
In the field of modern machinery and equipment, the application of microporous in enhancing the use of equipment performance and reliability and other aspects of the value is increasingly apparent. For example, in the key high-temperature components of aircraft engines, the application of microporous promotes the development of air film cooling technology, and effectively make up for the limitations of high-temperature-resistant materials to enhance the reliability and durability of the engine; in the field of internal combustion engines, the application of microporous design of injector nozzles not only significantly improves the effect of fuel atomization, but also plays an important role in improving combustion efficiency and effectively reducing harmful emissions. Therefore, the application of microporous not only promotes the development of greening technology, but also promotes the innovation of microporous machining technology and process, which makes the special machining technology such as electric discharge technology (EDM) [1], electrochemical machining (ECM) [2], and laser machining (LM) [3] become the mainstream microporous machining methods.  
  
−
As evidenced by the literature, agricultural machinery and automated guidance systems extensively leverage GNSS for navigation and positioning. However, a significant limitation of GNSS-centric approaches is their inability to dynamically perceive and respond to the immediate environment [16]. Furthermore, sole reliance on GPS proves unreliable within orchards due to signal degradation and multipath interference caused by dense tree canopies during in-row operation [17]. Standard GPS offers limited positional accuracy (typically 1-2 meters), insufficient for precise autonomous navigation. While centimeter-level accuracy solutions (e.g., RTK-GNSS) exist, their high cost presents a barrier. The economic viability of systems is further compromised when integrating other expensive sensors.
+
However, micro-hole machining technology based on special machining methods such as EDM, laser machining and electron beam is also facing some technical challenges. Due to the existence of the recast layer, the changes in its composition, structure, hardness and strength affect the performance of micro-holes in use, so scholars at home and abroad have carried out a wide range of white research in the removal of the recast layer and its effects. On the one hand, some scholars have deeply studied the formation mechanism of the recast layer, and while revealing the physical and chemical processes of the formation of the recast layer, they have also proposed the introduction of new processing media (e.g., nano-fluid, carnauba oil, etc.) [4,5] to adjust the processing environment [6,7] (e.g., temperature, pressure, etc.) and the development of new machining tools [8,9] and other means, which have effectively reduced the thickness of the recast layer; on the other hand, some scholars have reduced the formation and thickness of the recast layer by optimizing the process parameters [10,11] (e.g., current, voltage, and processing speed, etc.); in addition, some scholars have utilized post-processing techniques (e.g., chemical etching [12], ion-beam polishing [13], and electron-beam evaporation [14], as well as femtosecond laser technology, etc.) to achieve efficient removal of the recast layer and improve the microporosity. efficient removal and improved processing quality of micro-holes.  
  
−
Beyond localization, achieving full autonomy necessitates integrated environmental mapping and motion planning modules. Understanding the seamless interaction between these sub-systems is essential for the effective verification of overall control software. The inherent complexity of agricultural robotic vehicles, arising from diverse subsystems and demanding operational requirements, suggests that a model-based design (MBD) methodology offers a promising framework for current development efforts. While MBD is well-established and continually evolving within the automotive industry, particularly for embedded systems, its application in agricultural contexts presents distinct modeling and simulation challenges. Therefore, this paper details the development of a navigation control system for an orchard mobile robot utilizing a model-based design paradigm. The core objective is to create a robot capable of autonomous navigation in GNSS-restricted zones, employing minimal sensor interactions, computationally efficient algorithms, and requiring only minor modifications to its base platform configuration. The system leverages a localization strategy predicated on the provision of a pre-existing environmental map.
+
Despite this, some major problems remain. The formation of recast layers involves complex physical and chemical processes, including melting, solidification, and phase transformation of the material. These processes are influenced by a variety of factors, such as processing temperature, pressure, material composition etc. Their complexity makes it difficult in controlling the formation of recast layers. During micro-hole machining, the optimization of machining parameters is crucial to reduce the recast layer. However, finding the best combination of parameters is a challenging task due to the diversity of machining parameters and the coupling of interactions. In addition, the optimal parameters may be different for different materials and machining conditions, which further increases the difficulty of parameter optimization. Limitations of post-processing technologies: chemical etching may introduce new surface defects or contaminants, while ion and electron beams may be limited by equipment cost and operability, resulting in restricted form geometry of the processed object. The problem of the balance between processing efficiency and quality. In the process of micro-hole machining, there is a certain contradiction between improving the processing efficiency and guaranteeing the processing quality, in order to reduce the formation of recast layer, it may be necessary to reduce the processing speed or processing steps, but this will sacrifice the processing efficiency. Therefore, based on the characteristics of electrochemical light finishing processing, this paper proposes the concept of using electrochemical anodic dissolution to remove the recast layer, and the process method of electrochemical removal of recast layer is studied. Finally, a two-step lifting process method is proposed to complete the micro-hole orifice trimming processing on the basis of satisfying the high quality removal of the recast layer, so that it can meet the specific use performance requirements.  
−
 
+
==2. Experimental programming==
−
==2. System modelling and simulation==
+
===2.1 Formation mechanism and simulation of recast layer and its surface geometric characteristics===
−
 
+
====2.1.1 Formation mechanism and simulation of recast layer====
−
The robotic system depicted in '''Figure 1''' is configured as a four-wheel steering (4WS) vehicle, conceptually akin to a conventional automobile. Its operation is constrained to a two-dimensional (2D) planar domain, wherein idealized rolling motion is presumed in the absence of skidding. The robot’s state is formally defined within a configuration space <math>C</math> described by:
+
Laser processing is the result of the superposition of multiple single molten pools, so the recast layer formed by laser processing is inextricably linked to the formation of the single molten pool recast layer, the basic process of which is shown in [[Draft Seryazdan 514767809#img-1|Figure 1]](a). The material under a single pulsed laser irradiation is rapidly heated to the melting and boiling points, and melting and vaporization occur, forming a solid, liquid, and vapor three-phase coexistence. The melt flows along the walls of the processed area under a combination of vaporizing pressure and thermal influences, resulting in the formation of a concave contour of the melt pool that resembles a replica of the laser energy distribution curve. At the end of a single laser pulse, the vaporized metal in the center of the melt pool releases a large amount of thermal energy, which causes the melt attached to the walls of the melt pool and the curved melt at the bottom to be subjected to the recoil pressure of the metal vapor jet directly, which leads to the splashing of melt in the melt pool. Among them, part of the melt splashes out of the melt pool to form melt spatter, and accumulates at the edge of the melt pool to form a flying edge or burr, the simulation results are shown in [[Draft Seryazdan 514767809#img-1|Figure 1]](b); the other part of the melt will be deposited and attached to the surface of the inner wall of the melt pool,, and under the action of the combined coupling force, the melt will flow downward along the wall surface and reach a static equilibrium to form a smooth and excessive linear melt. After rapid cooling, the surface of the single molten pool forms a recast layer covered by a fused cladding after being subjected to a pressure gradient and a temperature gradient. The final laser process consists of the superposition of individual melt pools in the axial direction of the processing area and the formation of a recast layer with a periodic stream-like distribution on the surface of the hole wall.<div id="img-1"></div>
−
 
+
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;" 
−
{| class="formulaSCP" style="width: 100%;border-collapse: collapse;width: 100%;text-align: center;"  
+
|- style="background:white;"
 +
| style="text-align: center;padding:10px;" | [[Image:Draft_Seryazdan_636830651-image1.png|486px|link=https://www.scipedia.com/public/File:Draft_Seryazdan_636830651-image1.png]]
 
|-
 
|-
−
|
+
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;" | '''Figure 1'''. Schematic diagram of the simulation of recast layer formation
−
{| style="margin:auto;width: 100%;"
+
−
|-
+
−
| <math>C = (x,y,\psi ,\delta )</math>
+
−
|}
+
−
|  style="width: 5px;text-align: right;white-space: nowrap;"|(1)
+
 
|}
 
|}
 +
====2.1.2 Surface geometry of the recast layer====
 +
As shown in [[Draft Seryazdan 514767809#img-2|Figure 2]](a), at the surface of the initial melt pool, due to the large temperature gradient, the overflowed melt is mainly subject to Marangoni force, surface tension and gravity. The Marangoni force affects the flow of the melt, thus forming the shape of a domed dome; the surface tension and gravity in turn cause the overflowed melt to shrink outside the hole to form a ring-shaped accumulation.
  
−
<div id='img-1'></div>
+
As can be seen in [[Draft Seryazdan 514767809#img-2|Figure 2]](b) below, in the upper part of the inner wall of the micro-hole, the recast layer has a smooth surface and relatively low thickness but is unevenly distributed along the periphery of the hole. Because the steam action is the strongest here, the melt pool is shallow, the metal vapor expansion rate is unevenly distributed, and a large amount of molten metal is randomly discharged, but under the action of the Marangoni force, it shows a smooth and excessive gully shape. In the 1/3 position from the top of the orifice, the recast layer surface formed a turbulent ripple-like undulation, randomly distributed in the circumferential direction, the thickness of a relative increase in the molten metal was a localized layer accumulation. Because with the non-stop stacking of the molten pool, the pressure gradient and the molten liquid velocity increase, so that the molten liquid layer of the explosion, the small size of the fast particles and the large size of the liquid particles with small velocity successively excluded by spattering, the vapor flow still has a high recoil force but weakened in relation to the orifice. In the middle and lower part of the micro-hole, the flow on the surface of the recast layer tends to stabilize, and the flow direction is more consistent, but the thickness reaches the maximum; at the same time, the layer spacing decreases, and a large number of overlapping melts blown down by the gas stream appear in the cross-section. Because here the melt pool flow rate has been lower, the melt by gravity and surface tension to reach equilibrium, the formation of a large number of droplets of solute accumulation, and at the same time because of the convection of the melt pool so that the melt can not be quickly discharged and thus re-melting and condensation to form a thicker recast layer. At the bottom of the micro-hole, the surface of the recast layer shows an obvious insufficient flow, because the steam effect here is weakened, and the melt sputtering becomes the main mode of discharge to increase the viscosity of the melt, which leads to the formation of localized agglomerates. Overall, the surface geometry of the laser-processed recast layer shows a stable and continuous periodic stripe distribution, which is characterized by an orderly wave-like microstructure on the macroscopic level and a spherical dome distribution of "peaks and valleys" on the microscopic level.<div id="img-2"></div>
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"  
+
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
−
|-style="background:white;"
+
|- style="background:white;"
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image3.png|330px]]
+
| style="text-align: center;padding:10px;" | [[Image:Draft_Seryazdan_636830651-image2.png|600px|link=https://www.scipedia.com/public/File:Draft_Seryazdan_636830651-image2.png]]  
 
|-
 
|-
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 1'''. Schematic representation of the kinematic configuration employed in the four-wheel steering robotic platform
+
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;" | '''Figure 2'''. Simulation of surface geometric features of recast layer with SEM
 
|}
 
|}
−
 
+
====2.2 Design of experimental platforms====
−
In this study, a kinematic representation of the 4WS robotic platform has been adopted. Considering the regime of low-velocity traversal, and under the assumption that wheel velocity vectors align with the instantaneous direction of travel while tire forces remain negligible, a non-dynamic kinematic framework has been employed. The resultant formulation is expressed as:
+
Experimentally used electrolytic combination processing device shown in [[Draft Seryazdan 514767809#img-3|Figure 3]], the device has electrochemical processing module and three-coordinate displacement platform, the platform is equipped with <math display="inline">  X, Y, Z</math> three axes, three-axis linkage can be realized. <math display="inline"> z </math>-axis is equipped with electrochemical machining device, <math display="inline"> XY </math> motion platform is equipped with a work box, electrochemical removal processing in the work box. The working box is made of plexiglass and resin materials, which not only realizes the electrical insulation from the machine tool, but also facilitates the observation of the experimental process.<div id="img-3"></div>
−
 
+
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;" 
−
{| class="formulaSCP" style="width: 100%;border-collapse: collapse;width: 100%;text-align: center;"  
+
|- style="background:white;"
 +
| style="text-align: center;padding:10px;" | [[Image:Draft_Seryazdan_636830651-picture- 1.svg|center|600px|link=https://www.scipedia.com/public/File:Draft_Seryazdan_636830651-picture-_1.svg]]
 
|-
 
|-
−
|
+
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;" | '''Figure 3'''. Electrochemical light finishing processing experimental platform
−
{| style="margin:auto;width: 100%;"
+
−
|-
+
−
| <math>\begin{array}{*{20}{c}}
+
−
{}&{\dot x = vcos\left( {\psi  + \beta } \right)}\\
+
−
{}&{\dot y = vsin\left( {\psi  + \beta } \right)}\\
+
−
{}&{\dot \psi  = \frac{{vcos\beta }}{{{l_f} + {l_r}}}(tan{\delta _f} - tan{\delta _r})}\\
+
−
{}&{\beta  = arctan\left( {\frac{{{l_f}tan{\delta _r} + {l_r}tan{\delta _f}}}{{{l_f} + {l_r}}}} \right)}\\
+
−
{}&{\delta  = arctan\left( {\frac{{\omega ({l_f} + {l_r})}}{v}} \right)}\\
+
−
{}&{{\delta _f} =  - {\delta _r}}
+
−
\end{array}</math>
+
 
|}
 
|}
−
|  style="width: 5px;text-align: right;white-space: nowrap;"|(2)
+
===2.3 Design of experimental methodology===
−
|}
+
====2.3.1 Experimental flow design and preparation of samples====
−
 
+
The basic idea of the experiment, the laser was first used to process the prefabricated holes in the 2 mm thick metal plate, and then electrochemical processing was used to remove the recast layer on the hole wall, the specific process is shown in [[Draft Seryazdan 514767809#img-4|Figure 4]]. Laser parameters for the optimized parameters: pulse width of 0.2ms, peak power of 16kW, repetition frequency of 70Hz, drilling process along the laser head sprayed 0.6MPa argon to accelerate the exclusion of molten material, to reduce the burr, melt spattering and residual in the hole wall of the recast layer. Electrochemical processing, the use of motion control systems to insert the electrode wire centered in the pre-fabricated holes, detect whether the short circuit and set the pulse power parameters. First turn on the electrolyte pump, wait for the electrolyte to flow evenly through the hole and see a clear and stable liquid column at the exit, turn on the pulse power supply to start electrolysis, observe the experimental phenomena and power supply parameter changes, and turn off the power supply according to the set electrolysis time. The electrolyte is a neutral solution configured with pure water, and the dynamic liquid flushing method is used. In the experiment, considering the experimental error, 3 holes were processed under each parameter, and after the completion of the processing, the samples were cleaned, polished and metallurgically corroded, and the micro-hole morphology was observed with a scanning electron microscope, and the pore diameter was observed and measured with an optical microscope, and the average value of the 3 holes' diameters was finally taken under the same parameter. The micro-hole morphology of the sample is shown in [[Draft Seryazdan 514767809#img-5|Figure 5]].<div id="img-4"></div>
−
Here, <math>\dot x</math> and <math>\dot y</math> designate the Cartesian coordinates of the geometric center located along the rear axle, while  ''v'' denotes the linear forward speed. The angular orientation of the vehicle is symbolized by  <math>\dot \psi </math>, with  <math>\dot \psi  = \omega </math> corresponding to the yaw rate. The angular displacements of the front and rear wheels are represented by <math>{\delta _f}</math> and  <math>{\delta _r}</math>, respectively, and their combined effect is consolidated in the equivalent steering angle <math>\delta</math>. These steering angles are designed to be equal in magnitude but directed oppositely across the front and rear wheel assemblies. The parameters <math>{l_f}</math> and <math>{l_r}</math> indicate the longitudinal distances from the vehicle’s center of mass to the respective axles. The parameter <math>\beta </math>, denoting the slip angle, is regarded as negligible in the context of low-speed locomotion, with similar assumptions applied to individual wheel side-slip angles.
+
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;" 
−
 
+
|- style="background:white;"
−
The range of admissible values for the steering configuration is constrained within the following interval:  <math>\delta  \in [ - {45^ \circ }, + {45^ \circ }]</math>, which defines the upper and lower bounds of the equivalent steering angle. This angle serves as a surrogate for representing the aggregate steering effect of both front and rear wheels as if a single wheel were positioned at each end. The equivalent angle is formulated as:
+
| style="text-align: center;padding:10px;" | [[Image:Draft_Seryazdan_636830651-image5-c.png|504px|link=https://www.scipedia.com/public/File:Draft_Seryazdan_636830651-image5-c.png]]
−
 
+
−
{| class="formulaSCP" style="width: 100%;border-collapse: collapse;width: 100%;text-align: center;"  
+
 
|-
 
|-
−
|  
+
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;" | '''Figure 4'''. Micro-hole machining process flowchart
−
{| style="margin:auto;width: 100%;"
+
|}<div id="img-5"></div>
 +
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
 +
|- style="background:white;"
 +
| style="text-align: center;padding:10px;" | [[Image:Draft_Seryazdan_636830651-image6.png|600px|link=https://www.scipedia.com/public/File:Draft_Seryazdan_636830651-image6.png]]
 
|-
 
|-
−
| <math>{\delta _{(r,f)}} = \frac{{{\delta _{iw}} + {\delta _{ow}}}}{2}</math>
+
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;" | '''Figure 5'''. Laser processing sample drawing
 
|}
 
|}
−
|  style="width: 5px;text-align: right;white-space: nowrap;"|(3)
+
====2.3.2 Determination of electrochemical processing method====
−
|}
+
In the electrochemical machining process, generally keep the processing current or processing voltage constant, with the increase of workpiece aperture, the electrolyte resistance increases gradually. When the current is constant, the voltage increases with the increase of the electrolyte resistance, and the current density decreases with the increase of the processed surface area when; when the voltage is constant, the current decreases with the increase of the electrolyte resistance, and the current density decreases rapidly with the decrease of the current and the increase of the processed surface area. In summary, it can be found that, when the voltage is constant, the decreasing trend of current density is greater than that of constant current, which is conducive to ensuring the processing efficiency in the early stage while ensuring the surface quality in the later stage of processing, so this paper adopts constant voltage for electrolytic processing.
−
 
+
====2.3.3 Selection of electrolyte in electrochemical processing====
 +
Electrolytic processing, the electrode potential applied at the interface between the workpiece and the solution is different, the workpiece processing surface is in a different state, NaNO<sub>3</sub> solution is a passive electrolyte, the polarization curve of the anode of the workpiece into a non-linear distribution, passivation area of the metal surface to form an adsorbed oxygen layer or an oxide layer, i.e., passivation film; and precipitation of the oxygen area of the workpiece and the interface of the solution at the OH- ions easy to oxidize, precipitation of oxygen, precipitation of O<sub>2</sub> easy to oxidation Metal surface, so that the workpiece processing surface at the passivation film becomes thicker. The passivation film is less conductive, which in turn reduces the processing current density and lowers the dissolution rate of the metal. The NaCl solution is an active electrolyte, and the polarization curve of the anode of the workpiece is linearly distributed. The activation capacity of Cl- in the solution is very strong, the anode surface in a variety of conditions are in the active state of low-value dissolution, does not produce passivation and its side reactions, so the metal dissolution rate is higher, but at the same time there is a serious stray corrosion, which seriously affects the machining accuracy. In order to improve the nonlinear dissolution characteristics of the electrolyte, improve the current efficiency, soften the passivation salt film, this paper adopts a certain concentration of NaNO<sub>3</sub> solution mixed with a certain proportion of NaCl solution, in order to improve the machining efficiency at the same time easier to achieve the uneven dissolution or uneven super-passivation of the dissolution state, so as to improve the machining quality of the workpiece.
 +
==3. Results and analysis of removal of recast layer and orifice reshaping based on electrochemical light leveling==
 +
===3.1 Effect of electrolysis parameters on the removal of recast layers===
 +
When constant voltage electrolysis is used, the appropriate voltage should be selected. Theoretically, when the electrolysis voltage increases, the amount of electricity passing through the surface increases and the electrolysis rate increases. The electrolysis products and heat in the processing gap also increase, increasing the flow resistance in the gap, resulting in a decrease in the flow of electrolyte, so that the ability to exclude electrolysis products and heat is reduced. When there is a serious imbalance between the two, abnormal phenomena such as evaporation, boiling, and cavitation will occur in the processing gap, leading to serious failures such as short circuits and scarring, resulting in the interruption of processing. In addition, with the increase in current density, the electric field strength around the electrode wire increases, the stray corrosion around the orifice is enhanced, and the orifice is not rounded after electrolysis. Therefore, the voltage increase should not destroy the above balance as a prerequisite for the given electrolytic processing conditions, need to choose a suitable voltage value. Take the electrolysis time of 30s, the electrolyte is the conductivity of 100.4ms/cm NaNO<sub>3</sub> and NaCl mixed solution solution, respectively, with a voltage of 3-18V (interval 3V) for the recast layer removal experiment.
  
−
where  <math>{\delta _{iw}}</math> and  <math>{\delta _{ow}}</math> denote the steering angles of the robot’s inner and outer wheels, respectively. This formulation remains valid under the assumption of symmetrical steering inputs, and the value of <math>\delta</math> is constrained to lie within a specified range, expressed as:
+
After the completion of the experiment, the experimental results are processed: take the amount of hole expansion after processing and surface roughness change value as the reference amount; different voltage electrolysis, the expansion of the hole diameter is different, take the median value of the hole diameter in the process of electrolysis (with the minimum voltage electrolysis hole median value) as the benchmark, and take the change in the quality of the processing before and after the processing as an auxiliary reference for processing rate.
  
−
{| class="formulaSCP" style="width: 100%;border-collapse: collapse;width: 100%;text-align: center;"  
+
From the [[Draft Seryazdan 514767809#img-6|Figure 6]], it can be seen that after the same time of electrolysis, the pore radius and electrolysis rate increased with the increase of electrolysis voltage. When the voltage is 15V, the recast layer is completely removed. At this time, the electrolysis current is 0.5 A. Calculation gives a minimum current density of 10.09 A/cm<sup>2</sup>. The mass change and pore radius change shown in [[Draft Seryazdan 514767809#img-6|Figure 6]] reflect that the electrolysis rate is approximately proportional to the voltage. When electrolysis removes the recast layer, the volume electrochemical equivalent <math>\omega</math> of the material is a constant value, and the oxidation reaction of Ni, Fe, Cr, and other elements in the material occurs, in which Ni, Fe, and Cr will be oxidized with multiple valences according to the current density, and when the current density is greater than, all three elements are oxidized to the cation with the highest valence, i.e., the current efficiency <math>\eta</math> is constant. When the electrolysis voltage is 6 V, the extension of the fitted primary curve can be found that the electrolysis rate is larger at this time. This is because when the current density is small, Ni, Fe, Cr elements are partially oxidized to low valence cations, at this time the current efficiency <math>\eta</math> is larger, and the proportion of high valence oxidation of these three elements increases with the increase of current density, that is, the current efficiency decreases with the increase of current density.<div id="img-6"></div>
 +
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;" 
 +
|- style="background:white;"
 +
| style="text-align: center;padding:10px;" | [[Image:Draft_Seryazdan_636830651-image9.png|400px|link=https://www.scipedia.com/public/File:Draft_Seryazdan_636830651-image9.png]]
 
|-
 
|-
−
|  
+
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;" | '''Figure 6'''. Plot of the effect of voltage parameters on the removal of recast layer processing
−
{| style="margin:auto;width: 100%;"
+
|}[[Draft Seryazdan 514767809#img-7|Figure 7]] shows the SEM and metallographic images of the control holes and after removal of the recast layer by light-needle processing, from which it can be seen that the holes are rounded after light-finishing processing, and the recast layer is completely removed and the hole wall is smooth. When the constant pressure finishing process, the higher the voltage, the higher the current density, the higher the electrolysis rate. But at the same time as the voltage increases due to the hole entrance surface near the tool cathode, the electric field effect than other parts of the General Assembly serious stray corrosion, and because the entrance surface to increase the auxiliary anode, and by providing a potential difference to change the direction of the electric field of the anode entrance surface to reduce the entrance of the stray corrosion, effective control of electrochemical reaction of the hole entrance near the upper surface of the hole inlet, practical electrolytic machining, generally according to the cut-off In actual electrolytic processing, the voltage is generally determined according to the cut-off voltage and the electrolytic processing area. Under the condition of ensuring the processing surface quality, the electrolytic voltage can be increased in order to obtain a higher electrolytic rate, and the electrolyte flow rate can be increased at the same time in order to meet the exclusion of electrolytic processing products and heat.<div id="img-7"></div>
 +
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
 +
|- style="background:white;"
 +
| style="text-align: center;padding:10px;" | [[Image:Draft_Seryazdan_636830651-image10.png|600px|link=https://www.scipedia.com/public/File:Draft_Seryazdan_636830651-image10.png]]
 
|-
 
|-
−
| <math>{\delta _{min}} \le \delta  \le {\delta _{max}}</math>
+
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;" | '''Figure 7'''. SEM and metallographic images after removal of the recast layer
 
|}
 
|}
−
|  style="width: 5px;text-align: right;white-space: nowrap;"|(4)
+
===3.2 Effect of pulsed power supply on the removal of recast layers===
−
|}
+
The traditional DC electrolytic machining has a strong ability to scatter etching and a weak ability to centralized etching, which affects the accuracy of electrolytic machining, the general three-dimensional surface molding accuracy of 0.2 to 0.5 mm, and the hole machining molding accuracy of 0.025 to 0.05 mm. High-frequency, narrow pulse electrolytic machining can achieve high precision (dimensional accuracy less than 5<math>\mu</math>m, surface roughness less than 0.03mm), small gap (10 to 50<math>\mu</math>m) machining, machining quality is greatly improved. The principle of pulse electrolytic processing is to replace the continuous DC power supply with periodic intermittent power supply, and the anode undergoes periodic intermittent dissolution in the electrolyte. It uses the intermittent depolarization of the pulse gap with power failure to dissipate heat from the workpiece, and the electrochemical properties, flow field, and electric field of the machining gap are restored to the starting state. Pulse current electrolysis, the gap produces hydrogen pressure wave synchronized with the pulse current, the frequency and intensity with the increase of pulse frequency and enhancement, which strengthens the stirring effect on the electrolyte, so that the flow field distribution in the gap tends to be uniform, and to improve the heat dissipation conditions in the gap, so as to make the minimum stable machining gap is greatly reduced, and thus to enhance the fixed-domain nature of electrolytic machining. Therefore, this paper compares the difference between the processing quality of pulse power supply and DC power supply, and finally chooses the processing method of pulse current electrolysis to get a higher electrolysis rate under the premise that the processing quality can be guaranteed.
−
==3. Controller design architecture==
+
−
 
+
−
The controller software architecture delineates the high-level structure of constituent modules and their inter-module interactions. As illustrated in '''Figure 2''', the robot’s navigational control system is fundamentally structured around three core computational modules: the path planner, the motion planner, and the vehicle controller. This integrated navigation algorithm is implemented exclusively within the MATLAB® and Simulink® simulation environment.
+
  
−
<div id='img-1'></div>
+
As can be seen from [[Draft Seryazdan 514767809#img-8|Figure 8]](a), the surface quality obtained after processing with DC as the processing power source is relatively rough, the recast layer is not completely removed, and the electrochemical dissolution effect is small, and because of the DC electrolytic processing scattering corrosion ability is strong, so that the stray corrosion area is larger and the corrosion effect is more obvious, and at the same time, due to the fact that by-products can't be eliminated in time during the DC processing and electrolytic solution can't be renewed in time, which makes the local resistance increase, resulting in the inner wall of the small holes in part of the recast layer was not removed. As can be seen from [[Draft Seryazdan 514767809#img-8|Figure 8]](b), the use of pulsed current as the power supply processing after the surface is more smooth, the recast layer is completely removed and the processing quality is relatively stable, effectively solving the problems arising from the DC power supply, and further improving the quality and stability of the processing of electrolytic removal of the recast layer.<div id="img-8"></div>
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"  
+
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
−
|-style="background:white;"
+
|- style="background:white;"
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image40.png|480px]]
+
| style="text-align: center;padding:10px;" | [[Image:Draft_Seryazdan_636830651-image11.png|600px|link=https://www.scipedia.com/public/File:Draft_Seryazdan_636830651-image11.png]]  
 
|-
 
|-
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 2'''. Hierarchical control architecture devised for autonomous navigational decision-making
+
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;" | '''Figure 8'''. Comparison chart of AC power supply and DC power supply
 
|}
 
|}
 +
===3.3 Influence of cathodic lifting method on orifice reshaping===
 +
In order to further improve the machining effect of micro small hole workpieces, a staged combination of processing methods is proposed, based on the electrolytic removal of the recast layer, in the same station to further complete the small hole electrolytic repair of the machining method, i.e., cathode lifting method. The method is as follows: in the first stage, the surface quality of the workpiece is rapidly improved and the surface roughness is reduced by relatively large voltage processing to ensure the rapid removal of the recast layer; in the second stage, after the completion of the removal of the recast layer, the electric field distribution is influenced by changing the electrode position and the relatively small voltage is used for the trimming process to obtain a better surface quality and to realize the goal of the trimming of the micro-hole aperture. Due to the use of hybrid electrolyte, as mentioned above, the electrolyte has the characteristic of cutting the gap, when using small voltage processing, this time the inner wall of the hole although the current through, but the anode does not dissolve, the current efficiency is 0, which has been processed to protect the wall of the hole at the same time as the hole inlet trimming the shape of the hole to make the micro-hole has a better to meet the demand for the performance of the use of the micro-hole. Based on the above research, the experimental process parameters are as follows: the electrolyte used is a mixed solution of NaNO<sub>3</sub> and NaCl with a conductivity of 100.4ms/cm, the electrolysis voltage is 4v, and the electrolysis time is 20s.
  
−
The path planning module processes environmental imagery, translating it into a binary probabilistic map representing navigable space. Specifically, satellite imagery sourced from providers like Google is converted into this occupancy grid format, which subsequently serves as the foundational spatial representation for both robot navigation and self-localization tasks. This generated map explicitly demarcates traversable regions from non-drivable areas (e.g., obstacles, boundaries) within the operational environment. Leveraging this grid map, the module derives an optimal navigable trajectory for the robot. Detailed exposition of the specific path generation algorithms employed is omitted here, as it constitutes a distinct research domain beyond the present article’s scope. Upon successful path computation, this module outputs the requisite sequence of driving coordinates essential for guiding the robot through the designated environment.
+
From the [[Draft Seryazdan 514767809#img-9|Figure 9]](a) can be seen, without improving the processing method workpiece due to the over-processing phase of the surface obtained on the more rough and micro-hole expansion obvious, poor machining locality, taper relative to the [[Draft Seryazdan 514767809#img-9|Figure 9]](b) is greater, at the same time, the effect of repairing the shape of the micro-hole can not meet the demand for the use of the performance of the micro-hole is not obvious; from the [[Draft Seryazdan 514767809#img-9|Figure 9]](b) can be seen, after the elevation of the method of low-pressure combination of machining, the inner wall of the hole in the cut off gap characteristics of the end of the end of the protection of the dissolution occurred, the machining of locality Higher, the height of the surface bulge is reduced, the surface of the workpiece becomes relatively flat, the taper relative to the [[Draft Seryazdan 514767809#img-9|Figure 9]](a) has obvious improvement, while the effect of the repair effect is good, can meet the functional requirements of the micro-hole.<div id="img-9"></div>
−
 
+
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;" 
−
The vehicle controller actuates the commands generated by the motion planner module. It translates the computed linear and angular velocity setpoints into specific translational velocity and steering angle commands appropriate for the target robotic platform. These actionable directives are transmitted to the physical robot via a dedicated data communication interface. Crucially, sensor feedback – including wheel encoder data and steering angle measurements – is relayed back to the path tracking controller, enabling continuous closed-loop correction to maintain the desired trajectory under kinematic constraints.
+
|- style="background:white;"
−
 
+
| style="text-align: center;padding:10px;" | [[Image:Draft_Seryazdan_636830651-image12.png|600px|link=https://www.scipedia.com/public/File:Draft_Seryazdan_636830651-image12.png]]
−
===3.1 Lateral control design strategy===
+
−
 
+
−
To ensure strict adherence to the pre-defined navigation path, the implementation of an effective lateral control strategy is indispensable for governing vehicular steering dynamics. In the present study, robotic trajectory tracking has been facilitated through a pure pursuit control scheme, integrated with vehicle odometry data and a two-dimensional reference map. The realization of accurate navigation necessitates the simultaneous orchestration of both lateral and longitudinal control actions. Specifically, the steering control law—mathematically represented in Eq. (5)—is composed of a heading error correction (yaw/orientation compensation) and lateral position deviation suppression relative to the designated path:
+
−
 
+
−
{| class="formulaSCP" style="width: 100%;border-collapse: collapse;width: 100%;text-align: center;"  
+
 
|-
 
|-
−
|
+
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;" | '''Figure 9'''. Comparison of the results of the cathodic lift method
−
{| style="margin:auto;width: 100%;"
+
−
|-
+
−
| <math>{\delta _{str}} = Heading\;{\rm{error}} + Latera{l_\;}_{}{\rm{error}}</math>
+
−
|}
+
−
|  style="width: 5px;text-align: right;white-space: nowrap;"|(5)
+
 
|}
 
|}
 +
==4. Conclusions==
 +
In this paper, the use of electrochemical finishing processing method to remove the heavy casting layer left on the hole wall by laser processing and at the same time complete the orifice trimming processing can better meet the demand of micro-hole performance. Theoretical analysis and simulation of the formation mechanism of the recast layer and the surface geometrical features during laser processing were carried out, and experiments were carried out for the removal of the recast layer and orifice shaping, and small holes with the recast layer completely removed and the orifice rounded were obtained. Based on the experimental results, the following conclusions were obtained:
  
 +
1. Laser processing is made by a single molten pool superimposed in the axial direction of the processing area, the molten material remaining in the molten pool in the combined force coupling role in the formation of a smooth excess of linear melt, and in the rapid cooling of the single molten pool surface in the pressure gradient and the temperature gradient, the formation of a recast layer covered by the fusion layer. The surface geometry of the laser-processed recast layer shows a stable and continuous periodic stripe distribution, which is characterized by an ordered wave-like microstructure on the macro level and a spherical dome distribution of "peaks and valleys" on the micro level.
  
−
The heading error  <math>{\psi _e}</math> is defined as the angular deviation between the target path orientation  <math>{\psi _{desired}}</math> and the robot’s actual heading  <math>{\psi _{vehicle}}</math>, whereas the lateral error quantifies the perpendicular displacement between the vehicle’s center of gravity and the reference trajectory:
+
2. Current density is an important parameter affecting the electrolysis rate. When using mixed solution finishing processing recast layer, the current density is greater than 10.09A/cm<sup>2</sup>, the current efficiency remains unchanged, and the electrolysis rate is proportional to the electrolysis voltage. When the actual processing, the current density is too large easily lead to processing area scarring, short circuit and other quality defects. Therefore, according to the current density greater than 10.09A/cm<sup>2</sup> and electrolytic processing area to determine the current voltage, according to the electrolyte flow rate to increase the voltage to obtain a higher efficiency of finishing processing.
  
−
{| class="formulaSCP" style="width: 100%;border-collapse: collapse;width: 100%;text-align: center;"
+
3. When the electrolyte with the same conductivity is used under constant pressure processing conditions, the surface quality of the surface processed with the mixed electrolyte of NaNO<sub>3</sub> and NaCl is good, and the recast layer is completely removed; while the surface processed with the electrolyte of NaCl is seriously corroded by stray corrosion, and the recast layer is not completely removed.
−
|-
+
−
|
+
−
{| style="margin:auto;width: 100%;"
+
−
|-
+
−
| <math>\left\{ {\begin{array}{*{20}{l}}
+
−
{{\psi _e} = {\psi _{desired}} - {\psi _{vehicle}}}\\
+
−
{{e_{ra}} = {V_x}sin\psi  + {V_y}cos\psi }
+
−
\end{array}} \right.</math>  
+
−
|}
+
−
|  style="width: 5px;text-align: right;white-space: nowrap;"|(6)
+
−
|}
+
  
 +
4. The pulse effect in pulse finishing, the passivation of the anode of the workpiece, the stirring effect of the hydrogen pressure wave and the maintenance of the stability of the flow and electric fields during the power-off gap play a key role in enhancing the surface quality of the finish after the removal of the recast layer by the finishing process.
  
−
Here,  <math>{V_x}</math> and  <math>{V_y}</math> respectively represent the vehicle’s longitudinal and lateral velocity components. As detailed in Section 2, under the employed four-wheel steering (4WS) configuration—illustrated in '''Figure 3'''—the lateral velocity component is considered negligible at low speeds to facilitate optimal steering precision. Consequently, Eq. (7) may be reexpressed as:
+
5. When the cathodic lifting method is used to process the micro-hole, the truncation effect is utilized so that the inner wall surface of the micro-hole will not be processed twice while the orifice is trimmed to achieve the shape of the process, and ultimately the inner wall is smooth and the orifice is rounded to obtain a micro-hole with better usability.
−
 
+
==Acknowledgements==
−
{| class="formulaSCP" style="width: 100%;border-collapse: collapse;width: 100%;text-align: center;"
+
This work was supported by Application of corrosion protection and online monitoring technology based on chlor-alkali industry (ZYYD2023B03).
−
|-
+
−
|
+
−
{| style="margin:auto;width: 100%;"
+
−
|-
+
−
| <math>{\delta _{str}} = {V_x}sin\psi  + {\psi _{desired}} - {\psi _{vehicle}}</math>
+
−
|}
+
−
|  style="width: 5px;text-align: right;white-space: nowrap;"|(7)
+
−
|}
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image49.png|360px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 3'''. Depiction of the elWobot’s inverse four-wheel steering configuration under zero lateral slip conditions
+
−
|}
+
−
 
+
−
This specific control regime, wherein the lateral slip is eliminated, is termed the Zero-side-slip maneuver, a condition characteristically achieved under reduced velocity conditions. Under such circumstances, the heading angle  <math>\gamma </math> is equated with the vehicle’s course direction  <math>\psi</math>, i.e., the actual trajectory orientation:
+
−
 
+
−
{| class="formulaSCP" style="width: 100%;border-collapse: collapse;width: 100%;text-align: center;"
+
−
|-
+
−
|
+
−
{| style="vertical-align: top;margin:auto;width: 100%;"
+
−
|-
+
−
| <math>\gamma  = \psi  + \beta </math>
+
−
|}
+
−
|  style="vertical-align: top;width: 5px;text-align: right;white-space: nowrap;"|(8)
+
−
|}
+
−
 
+
−
 
+
−
However, due to physical constraints imposed by steering geometry and the attainable side-slip angle  <math>\beta </math> , the permissible steering angle  <math>{\delta _{str}}</math> required for trajectory realization is bounded as follows:
+
−
 
+
−
{| class="formulaSCP" style="width: 100%;border-collapse: collapse;width: 100%;text-align: center;"
+
−
|-
+
−
|
+
−
{| style="vertical-align: top;margin:auto;width: 100%;"
+
−
|-
+
−
| <math>\psi  - {\beta _{\max }} \le {\delta _{str}} \le \psi  + {\beta _{max}}</math>
+
−
|}
+
−
|  style="vertical-align: top;width: 5px;text-align: right;white-space: nowrap;"|(9)
+
−
|}
+
−
 
+
−
Alternatively, Eq. (10) provides the steering angle condition necessary to achieve the desired orientation alignment for trajectory following.
+
−
 
+
−
{| class="formulaSCP" style="width: 100%;border-collapse: collapse;width: 100%;text-align: center;"
+
−
|-
+
−
|
+
−
{| style="margin:auto;width: 100%;"
+
−
|-
+
−
| <math>\psi  - {\beta _{max}} \le {\delta _{str}} \le \psi  + {\beta _{max}}</math>
+
−
|}
+
−
|  style="width: 5px;text-align: right;white-space: nowrap;"|(10)
+
−
|}
+
−
 
+
−
The configuration illustrated in '''Figure 3''' represents the elWobot in a 4WS-negative alignment during the Zero-side-slip maneuver.
+
−
 
+
−
Due to limitations in sensor-based localization, the robot’s actual heading '''𝜓''' is inferred indirectly via its steering angle and velocity. The heading error is regulated by the PID controller, which is structured as a nonlinear, discrete-time single-input single-output (SISO) system constrained by predefined saturation bounds:
+
−
 
+
−
===3.2 Model-based PID controller tuning===
+
−
 
+
−
Effective controller implementation necessitates precise calibration of gain parameters to achieve optimal system performance. Post-design PID tuning constitutes a critical phase for determining ideal proportional, integral, and derivative coefficients that govern controller behavior. While conventional manual tuning remains prevalent, this approach demands considerable expertise from control engineers and frequently evolves into a protracted, iterative process. To circumvent these limitations, our research adopts an automated model-based tuning framework leveraging MATLAB/Simulink’s computational ecosystem. Specifically, we employ Simulink Control Design™ alongside the System Identification Toolbox™ to implement this data-driven methodology. The technique requires a linearized plant approximation, presenting implementation challenges for our inherently nonlinear robotic system. To address this, operational open-loop response datasets are acquired under controlled input conditions. These experimental datasets enable localized linearization within defined operational envelopes, permitting the PID tuner to construct region-specific transfer function approximations. Our implementation utilizes reference trajectory tracking with bounded output constraints during optimization, applying this standardized approach to both steering and velocity control subsystems. '''Figure 4''' illustrates this model-based workflow for steering control, where a dedicated plant model is empirically derived from robotic steering response characteristics. Subsequent system identification procedures generate the foundational transfer function model essential for PID coefficient optimization.
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image66.png|510px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 4'''. Steering controller calibration via model-informed PID parameter tuning
+
−
|}
+
−
 
+
−
The velocity control subsystem undergoes specialized tuning within the navigational velocity spectrum (0.45–2.25 m/s), reflecting operational boundary conditions. Strategic tuning prioritizes lower velocity regimes to prevent destabilization during slow-speed maneuvers while maintaining acceptable higher-speed responsiveness. As documented in '''Table 1''', the finalized gain parameters reflect platform-specific optimization for both control dimensions. Analysis of tuned responses reveals an intentional design compromise: Minor overshoot (observable in steering response plots) is deliberately preserved to enhance transient performance characteristics. Complete overshoot elimination induces excessive system lethargy, extending stabilization periods beyond functional requirements. Consequently, controller calibration embodies a deliberate equilibrium between dynamic responsiveness and stabilization precision—a fundamental tradeoff in transient performance optimization. This balance ensures adequate reference tracking agility without compromising operational stability, particularly crucial during trajectory execution under variable inertial conditions.
+
−
 
+
−
'''Table 1.''' Optimized gain parameters for PID-based regulation of velocity and steering dynamics
+
−
 
+
−
{| style="width: 100%;border-collapse: collapse;"
+
−
|-
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''Control'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''P'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''I'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''D'''
+
−
|-
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|'''Velocity'''
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|0.5106
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|2.153
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|-0.005
+
−
|-
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|'''Steering'''
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|1.35
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|3.537
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|0.30
+
−
|}
+
−
 
+
−
 
+
−
===3.3 Model integration===
+
−
 
+
−
The comprehensive navigation framework synthesizes unit-level and subsystem components into an integrated operational model. This architectural integration establishes deterministic data exchange protocols across functional segments, enabling holistic system validation. A significant advantage of this modular design lies in its cross-project reusability: Pre-validated components accelerate development cycles for future autonomous platforms. Debugging efficiency is substantially enhanced through fault isolation capabilities, allowing targeted module inspection rather than full-system analysis. As visualized in '''Figure 5''', the implemented robotic navigation system partitions functionality into four principal domains:
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image67.png|342px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 5'''. Fully integrated and operational model of the robotic navigation framework
+
−
|}
+
−
 
+
−
(1) Sensor Fusion Interface: Processes both live sensor streams and simulated inputs essential for localization. This includes ingestion of trajectory waypoint sequences generated by path planning algorithms.
+
−
 
+
−
(2) Motion Control Core: Embeds the Pure Pursuit tracking controller that computes steering directives using egocentric localization estimates and navigational waypoints. Pose data originates from odometric measurements correlated against prior path planning operations on occupancy grid maps. These environmental representations derive from georeferenced 2D raster workspace models.
+
−
 
+
−
(3) Kinematic Output Hub: Transmits derived velocity setpoints and steering directives to drive systems. Continuously monitors Euclidean distance to target coordinates, issuing null motion commands when the robot enters predefined terminal proximity thresholds.
+
−
 
+
−
(4) CAN Communication Gateway: Translates kinematic directives into Controller Area Network messages for actuator control. Incorporates diagnostic telemetry channels and failsafe triggers for real-time system health monitoring.
+
−
 
+
−
All computational processes execute within a rigorously enforced 10ms deterministic cycle. Since native Simulink® lacks inherent real-time capability, temporal synchronization is achieved through dedicated Real-Time Sync blocks. These enforce hardware-timed execution intervals that emulate embedded deployment conditions during simulation. The fail-safe subsystem autonomously triggers protective shutdown protocols upon detecting critical anomalies, including actuator faults or deviation beyond safe operating envelopes. Diagnostic messaging provides continuous state observability through standardized SAE J1939 telemetry frames. This temporal formalization ensures controller outputs maintain phase alignment with sensor inputs - a critical requirement for closed-loop stability during high-speed navigation. The synchronized execution environment further enables valid performance benchmarking against real-world timing constraints prior to physical deployment.
+
−
 
+
−
==4. Simulation results and discussion==
+
−
 
+
−
This segment presents empirical validation results for the elWObot robotic platform’s navigation controller through co-simulation and field trials. The integrated development framework leveraged MATLAB/Simulink for model-based design, incorporating both virtual simulation and hardware-in-the-loop (HIL) verification. Successful algorithm deployment occurred in unstructured outdoor environments, specifically cobblestone pathways and densely vegetated terrain engineered to simulate agricultural field irregularities and off-road conditions. Under these challenging substrates, the system exhibited consistently reliable operational performance and trajectory adherence.
+
−
 
+
−
===4.1 Robot velocity response===
+
−
 
+
−
Performance characterization was conducted at a target operational velocity of 1 m/s within the Wenzhou Vocational College of Science and Technology. While orchard validation remains pending platform refinements, the AST terrain provided sufficient stochastic disturbances for preliminary evaluation. '''Figure 6''' demonstrates the optimized velocity tracking behavior, with model execution at 10ms intervals contrasting with 200ms CAN bus update cycles. The PID controller exhibits characteristic transient dynamics: an intentional overshoot to 1.1 m/s occurs within the initial 200ms, subsequently decaying exponentially to converge within ±1% of the setpoint at t=1s. This overshoot magnitude constitutes a deliberate design parameter to overcome stiction-induced torque requirements at the wheel-terrain interface. Actual velocity feedback (measured via wheel encoders) demonstrates second-order following behavior, achieving asymptotic stability at t=1.8s with near-zero steady-state error. Segments A-C confirm consistent tracking fidelity during sustained operation without observable oscillation. Though enhanced disturbance rejection could theoretically be achieved through gain elevation, such tuning induces hypersensitivity to inertial perturbations and reduces stability margins. Consequently, the implemented PID configuration represents an optimal compromise between transient acceleration capability and robust velocity regulation.
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image68.png|492px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 6'''. Temporal response of the robot’s velocity following PID gain optimization
+
−
|}
+
−
 
+
−
===4.2 Robot steering response===
+
−
 
+
−
To evaluate directional control fidelity, the elWObot executed pre-mapped trajectories at its optimized operational velocity of 1 m/s (established in Section 4.5 following comparative velocity trials). All turning maneuvers were digitally recorded and synchronously compared against commanded steering inputs and actuator responses. During critical testing sequences observed from the vehicle’s frontal perspective, the robotic system initiated right-turn maneuvers. Leveraging its four-wheel-independent-steering (4WS) architecture, the platform implemented negative-phase coordination where front and rear axles counter-steered to minimize turning radius. As evidenced in '''Figure 7''', the steering controller effectively translated reference inputs (Str_PID_input) into wheel-angle outputs while maintaining Ackermann-compliant kinematics. This necessitates greater deflection of inner wheels relative to outer wheels during curvature negotiation - a behavior confirmed by rear-left wheel (RL_deg) consistently exceeding rear-right wheel (RR_deg) angular displacement.
+
−
 
+
−
Initial turn execution demonstrated exceptional tracking performance across all wheels. Subsequent maneuvers, however, revealed a systematic discrepancy at extreme steering demands: the inner wheel plateaued at 42°±0.5° tolerance versus the 45° command input ('''Figure 7'''). This limitation stems from inherent kinematic boundaries hard-coded during developmental modeling, where ±42° constitutes the mechanical steering stop. Consequently, the control algorithm intentionally clamps inputs at 45° to emulate physical stops with operational margin. Additional signal phase offsets observed between commanded and achieved angles derive from deterministic CAN bus communication latency operating at 200ms cycles. Comprehensive wheel-angle trajectories during transitional states appear in '''Figure 8''', further validating the 42° saturation threshold. Crucially, sideslip angle (β) variations remained below 1.2° throughout testing ('''Figure 9'''), exhibiting negligible influence on vehicle orientation or steering dynamics per Eqs. 2 and 15. This insensitivity confirms the theoretical advantage of negative-phase 4WS over conventional 2WS systems in slip mitigation. Persistent β offsets of 0.3°±0.1° originated from minor wheel-alignment inconsistencies at neutral positions, though these remained within operational tolerances for agricultural contexts.
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image69.png|444px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 7'''. Steering angle dynamics in response to PID-regulated input signals
+
−
|}
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image70.png|444px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 8'''. Multi-wheel steering angle response elicited by the applied control input
+
−
|}
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image71.png|444px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 9'''. Quantitative evaluation of the robot’s sideslip angle (β) during maneuvering
+
−
|}
+
−
 
+
−
===4.3 Robot yaw response===
+
−
 
+
−
'''Figure 10''' demonstrates close correlation between simulated yaw predictions and experimentally measured yaw rates during trajectory execution. Initial conditions established the robot’s heading at ψ₀ = 180° (π radians) relative to magnetic north. Throughout linear navigation from t=0–200s, both datasets maintained directional stability with angular deviations below ±0.5°. A deliberate 10° yaw rate perturbation introduced at t=200s was accurately replicated in the simulation model within 0.3° RMS error. This tracking fidelity persisted during subsequent maneuvers, with synchronized responses observed at t=480s when commanded directional changes occurred. Here, the simulation registered a 90° orientation shift while physical constraints limited the actual yaw rate to 45° – a discrepancy attributable to steering linkage saturation.
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image72.png|408px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 10'''. Comparative analysis of simulated versus empirical yaw rate responses
+
−
|}
+
−
 
+
−
Fundamental to this analysis is the established sign convention: positive values denote counterclockwise rotation (viewed top-down), while negative values indicate clockwise motion. The simulation’s negative yaw manifestation at t=760s correctly represented the vehicle’s reversed directional state upon path completion. Notably, the platform returned to its initial geospatial coordinates but with inverted orientation (heading = -180°), confirming successful loop closure despite directional reversal. This terminal state aligns with conventional vehicle dynamics frameworks where magnetic north corresponds to 0° yaw. The persistent 180° offset throughout testing originated from intentional initialization parameters rather than measurement drift, as confirmed by post-mission inertial validation. Kinematic discrepancies at extreme steering demands (e.g., t=480s) highlight the model’s capacity to capture saturation effects inherent to physical systems.
+
−
 
+
−
===4.4 Robot navigation testing===
+
−
 
+
−
Conventional navigation strategies for car-like robotic platforms typically operate within reduced-configuration planar spaces defined solely by Cartesian x-y coordinates. '''Figure 11''' demonstrates trajectory execution within such an environment, simulating agricultural row-traversal behaviors including linear inter-row navigation and headland turning maneuvers. Path planning was implemented via Probabilistic Road Map (PRM) methodology on occupancy grid maps, where white regions denote navigable terrain and black zones represent obstructions. Notably, this approach disregards non-holonomic constraints inherent in wheeled platforms. The triangular representation in '''Figure 11''' illustrates the robot’s orientation during traversal at Wenzhou Vocational College of Science and Technology’ test facility. Velocity trials (0.5, 1.0, 1.5, 2.0 m/s) revealed optimal tracking fidelity at 1.0 m/s ('''Figure 11'''f), with comprehensive velocity-dependent analysis detailed in Section 4.5. Trajectory adherence was quantified through superimposed path visualization (blue trajectory), though Turn 4 exhibited corner-cutting behavior—manifesting as increased turning radius relative to waypoint positioning. This phenomenon stems from discretized path planning and non-holonomic limitations preventing instantaneous directional changes, necessitating minimum rotational radii. Such constraints are particularly pronounced in Ackermann-steered platforms (2WS/4WS) compared to differential/skid-steer systems capable of zero-radius turns. Mitigation strategies include implementing continuous-curvature path planners and optimizing pure pursuit controllers through velocity-adaptive lookahead distances.
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[File:20250620 174112.png|408x408px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 11'''. Real-world trajectory tracking of the robot along a predefined path at the AST test facility, Wenzhou Vocational College of Science and Technology
+
−
|}
+
−
 
+
−
Beyond qualitative assessment, rigorous quantitative evaluation examined linear tracking (Start → Turn 1) and turning performance across four maneuvers. '''Figure 12''' documents straight-line traversal errors bounded within ±0.05° tolerance, with transient overshoots attributable to surface-induced disturbances challenging controller robustness. Turning characteristics ('''Figure 11''') were statistically analyzed in '''Table 2''', revealing a maximum instantaneous peak error of 27% at Turn 1. Crucially, this metric represents localized deviation rather than holistic steering fidelity—a consequence of modeling simplifications where steering angle was computed as the absolute average of front-wheel displacements. Physical systems exhibit asymmetric wheel angles due to Ackermann kinematics, constraining achievable yaw rates. This approximation propagates to yaw estimation (Eq. 2), where velocity-dependent transients precede steady-state convergence. True maneuvering precision is better quantified by average angular offsets below 5° across all turns ('''Table 2'''). Negative steering values indicate leftward deflection, with kinematic saturation evidenced by the front-right wheel’s inability to achieve the 42.97° command angle—validating modeled mechanical limits.
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image74.png|450px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 12'''. Navigation performance of the robot during linear path traversal
+
−
|}
+
−
 
+
−
'''Table 2. '''Comparative metrics of steering input angles and corresponding yaw responses across multiple turning scenarios
+
−
 
+
−
{| style="width: 100%;border-collapse: collapse;"
+
−
|-
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''Turn'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''Peak Input angle (deg.)'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''Peak yaw angle (deg.)'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''Peak error (%)'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''Avg.offset (deg.)'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''FL angle'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''FR angle'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''RL angle'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''RR angle'''
+
−
|  style="border-top: 1pt solid black;border-bottom: 1pt solid black;vertical-align: top;"|'''Equivalent Steering angle'''
+
−
|-
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|1st
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|28.28
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|20.50
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|27.5
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|1.19
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|-24.10
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|-18.11
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|24.18
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|18.15
+
−
|  style="border-top: 1pt solid black;vertical-align: top;"|22.12
+
−
|-
+
−
|  style="vertical-align: top;"|2nd
+
−
|  style="vertical-align: top;"|38.42
+
−
|  style="vertical-align: top;"|33.04
+
−
|  style="vertical-align: top;"|14.0
+
−
|  style="vertical-align: top;"|3.06
+
−
|  style="vertical-align: top;"|-38.27
+
−
|  style="vertical-align: top;"|-25.57
+
−
|  style="vertical-align: top;"|38.45
+
−
|  style="vertical-align: top;"|25.60
+
−
|  style="vertical-align: top;"|32.18
+
−
|-
+
−
|  style="vertical-align: top;"|3rd
+
−
|  style="vertical-align: top;"|42.97
+
−
|  style="vertical-align: top;"|36.44
+
−
|  style="vertical-align: top;"|15.2
+
−
|  style="vertical-align: top;"|4.26
+
−
|  style="vertical-align: top;"|-41.95
+
−
|  style="vertical-align: top;"|-27.83
+
−
|  style="vertical-align: top;"|41.59
+
−
|  style="vertical-align: top;"|27.82
+
−
|  style="vertical-align: top;"|34.70
+
−
|-
+
−
|  style="vertical-align: top;"|4th
+
−
|  style="vertical-align: top;"|42.97
+
−
|  style="vertical-align: top;"|36.44
+
−
|  style="vertical-align: top;"|15.2
+
−
|  style="vertical-align: top;"|5.04
+
−
|  style="vertical-align: top;"|-41.95
+
−
|  style="vertical-align: top;"|-27.83
+
−
|  style="vertical-align: top;"|41.59
+
−
|  style="vertical-align: top;"|27.82
+
−
|  style="vertical-align: top;"|34.71
+
−
|-
+
−
|  style="vertical-align: top;"|5th
+
−
|  style="vertical-align: top;"|15.95
+
−
|  style="vertical-align: top;"|12.69
+
−
|  style="vertical-align: top;"|20.4
+
−
|  style="vertical-align: top;"|1.15
+
−
|  style="vertical-align: top;"|-13.95
+
−
|  style="vertical-align: top;"|-12.26
+
−
|  style="vertical-align: top;"|14.13
+
−
|  style="vertical-align: top;"|12.22
+
−
|  style="vertical-align: top;"|13.63
+
−
|-
+
−
|  style="vertical-align: top;"|6th
+
−
|  style="vertical-align: top;"|42.97
+
−
|  style="vertical-align: top;"|36.44
+
−
|  style="vertical-align: top;"|15.2
+
−
|  style="vertical-align: top;"|5.04
+
−
|  style="vertical-align: top;"|-41.95
+
−
|  style="vertical-align: top;"|-27.83
+
−
|  style="vertical-align: top;"|41.59
+
−
|  style="vertical-align: top;"|27.82
+
−
|  style="vertical-align: top;"|34.47
+
−
|-
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|7th
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|38.23
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|32.28
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|15.5
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|3.43
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|-38.25
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|-25.55
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|38.43
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|25.55
+
−
|  style="border-bottom: 1pt solid black;vertical-align: top;"|32.00
+
−
|}
+
−
 
+
−
 
+
−
===4.5 Controller tracking performance===
+
−
 
+
−
The path-tracking efficacy of the pure pursuit controller was rigorously assessed through steering angle discrepancy analysis during turning maneuvers. Systematic testing evaluated velocity profiles (0.5, 1.0, 1.5, 2.0 m/s) coupled with preview distances (0.75, 1.0, 1.2, 1.5, 2.2 m), with the maximum lookahead constrained to the robotic platform’s inter-axle dimension. Optimal operational parameters were determined through minimization of steering offset error – defined as the angular deviation between commanded steering input and realized yaw response. '''Figure 13''' presents quantile distribution plots of angular tracking discrepancies across turning sequences. Minimal median errors emerged at 1.0 m/s velocity with 0.75 m preview distance, attributable to velocity-dependent orientation dynamics: at this specific velocity, kinematic constraints yielded near-ideal alignment between steering commands and platform heading. Suboptimal velocities induced systematic overcompensation (>1.0 m/s) or underresponsiveness (<1.0 m/s), degrading trajectory adherence. Notably, reduced preview distances consistently outperformed longer horizons across velocity regimes.
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image75.png|450px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 13'''. Distributional analysis of steering offset errors across seven distinct turning maneuvers under varying velocity and look-ahead configurations: (a) 0.75 m look-ahead, 0.5 m/s velocity; (b) 1.0 m look-ahead, 0.5 m/s velocity; (c) 1.2 m look-ahead, 0.5 m/s velocity; (d) 1.5 m look-ahead, 0.5 m/s velocity; (e) 2.2 m look-ahead, 0.5 m/s velocity; (f) 0.75 m look-ahead, 1.0 m/s velocity; (g) 0.75 m look-ahead, 1.5 m/s velocity; (h) 0.75 m look-ahead, 2.0 m/s velocity
+
−
|}
+
−
 
+
−
Analysis of the optimal configuration ('''Figure 13'''f) reveals near-zero median errors for most turns, with exceptions at Turns 4 and 6. These anomalies stem from Ackermann steering limitations during acute maneuvers, where physical saturation prevented attainment of required wheel angles. The resultant kinematic discontinuity generated accumulated heading offsets and statistical outliers. Additional error variance in '''Figure 13'''f derives from sensor latency and transient noise artifacts during high-curvature transitions.
+
−
 
+
−
'''Figure 14''' employs Taylor’s statistical framework to quantify controller performance during turning sequences, correlating reference steering inputs with measured yaw responses [18]. Controller efficacy was benchmarked against three criteria: (1) Normalized root-mean-square difference (RMSD) approaching zero, (2) Normalized standard deviation approximating unity, and (3) Correlation coefficients nearing maximum values.
+
−
 
+
−
<div id='img-1'></div>
+
−
{| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
+
−
|-style="background:white;"
+
−
|style="text-align: center;padding:10px;"| [[Image:Draft_Wu_280690876-image76.png|450px]]
+
−
|-
+
−
| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 14'''. Normalized Taylor diagram illustrating controller efficacy across diverse turning conditions during autonomous navigation
+
−
|}
+
−
 
+
−
Experimental data demonstrates robust performance: RMSD values cluster within 0.2–0.4 across maneuvers, while standard deviations converge near 0.85. Correlation coefficients exceeding 0.99 confirm exceptional command-response synchronization. This statistical constellation – minimal RMSD, near-unity standard deviation, and maximal correlation – validates the controller’s proficiency in negotiating curvilinear paths despite kinematic limitations and environmental disturbances.
+
−
 
+
−
==5. Conclusion==
+
−
 
+
−
This study addresses the critical challenge of robotic navigation in dense orchard settings where GNSS/GPS signal degradation impedes localization capabilities. We present a model-driven framework for developing navigation architectures tailored to Ackermann-constrained mobile platforms operating under such conditions. The solution employs a modular decomposition strategy, with dedicated subsystems for: (1) Probabilistic motion planning; (2) Nonlinear vehicle control; (3) Sensor-fused localization; (4) Robust data telemetry.
+
−
 
+
−
This compartmentalized design accelerated iterative development and validation cycles. Our integrated navigation model synthesizes trajectory generation outputs with vehicular kinetic constraints to produce executable motion primitives. The core innovation lies in decoupling velocity regulation from heading control - requiring only proprioceptive inputs from wheel encoders and steering resolvers. This sensor-minimal approach significantly reduces exteroceptive sensing dependencies while maintaining navigation integrity in constrained environments. Rigorous verification was conducted through co-simulation in MATLAB/Simulink environments, followed by field trials on a scaled robotic platform. The architecture demonstrated exceptional path-tracking fidelity during both linear transits and curvilinear maneuvers across varied terrain. Systematic velocity sweeps revealed optimal operational performance at 1 m/s, where platform yaw dynamics exhibited near-perfect correspondence with steering geometry kinematics. This velocity-specific synchronization minimized cumulative heading deviations observed at other test speeds (0.5, 1.5, 2.0 m/s).
+
−
 
+
−
Current investigations focus on enhancing environmental adaptability through tight coupling of inertial navigation systems with online path optimization routines. This sensor-fusion strategy aims to boost robustness against orchard-specific disturbances including: canopy occlusion effects, terrain-induced wheel slip, and foliage multipath artifacts. Subsequent research phases will validate reliability metrics under extended operational durations in commercial orchard deployments.
+
−
 
+
−
==Acknowledgement:==
+
−
 
+
−
'''Funding Statement: '''None.
+
−
 
+
−
'''Author Contributions: '''The authors confirm contribution to the paper as follows: Study conception and design: Li Tian, Xingjia Pan; Data collection: Li Tian; Analysis and interpretation of results: Li Tian, Xingjia Pan; Draft manuscript preparation: Li Tian, Xingjia Pan. All authors reviewed the results and approved the final version of the manuscript.
+
−
 
+
−
'''Ethics Approval: '''Not applicable.
+
−
 
+
−
'''Conflicts of Interest: '''The authors declare no conflicts of interest to report regarding the present study.<span id="RefSection"></span>
+
−
 
+
 
==References==
 
==References==
 +
<div class="auto" style="text-align: left;width: auto; margin-left: auto; margin-right: auto;font-size: 85%;">
  
−
[1] Oberti R, Shapiro A. Advances in robotic agriculture for crops. Biosyst Eng. 2016;100(146):1–2.
+
[1] Han L., Sartin M.M., Tian Z.-Q., Zhan D., Tian Z.-W. Electrochemical nanomachining. Curr. Opin. Electrochem., 22:80–86, 2020.
−
 
+
−
[2] Koh KC, Cho HS. A path tracking control system for autonomous mobile robots: an experimental investigation. Mechatronics. 1994;4(8):799–820.
+
−
 
+
−
[3] Bac CW, Van Henten EJ, Hemming J, Edan Y. Harvesting robots for high-value crops: State-of-the-art review and challenges ahead. J Field Robot. 2014;31(6):888–911.
+
−
 
+
−
[4] Reina G, Milella A, Rouveure R, Nielsen M, Worst R, Blas MR. Ambient awareness for agricultural robotic vehicles. Biosyst Eng. 2016;146:114–32.
+
−
 
+
−
[5] Verbiest R, Ruysen K, Vanwalleghem T, Demeester E, Kellens K. Automation and robotics in the cultivation of pome fruit: Where do we stand today? J Field Robot. 2021;38(4):513–31.
+
  
−
[6] Wang T, Chen B, Zhang Z, Li H, Zhang M. Applications of machine vision in agricultural robot navigation: A review. Comput Electron Agric. 2022;198:107085.
+
[2] Sisodiya M.S., Shukla S., Bajpai V. Feasibility analysis of novel Maglev EDM by comparing with conventional micro EDM. Sci. Rep., 12, 2613, 2022.
  
−
[7] Blok P M, van Boheemen K, van Evert F K, IJsselmuiden J, Kim G H. Robot navigation in orchards with localization based on Particle filter and Kalman filter. Comput Electron Agric. 2019;157:301–10.
+
[3] Schmidt M., et al. Advances in macro-scale laser processing. CIRP Ann., 67:719–742, 2018.
  
−
[8] Schwarting W, Alonso-Mora J, Rus D. Planning and decision-making for autonomous vehicles. Annu Rev Control Robot Auton Syst. 2018;1(1):187–210.
+
[4] Wang X., et al. Nanofluids application in machining: a comprehensive review. Int. J. Adv. Manuf. Technol., 131:3113–3164, 2024.
  
−
[9] Bechar A, Vigneault C. Agricultural robots for field operations: Concepts and components. Biosyst Eng. 2016;149:94–111.
+
[5] Kozak J., Rozenek M., Dabrowski L. Study of electrical discharge machining using powder-suspended working media. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 217:1597-1602, 2003.  
  
−
[10] Winterhalter W, Fleckenstein F, Dornhege C, Burgard W. Localization for precision navigation in agricultural fields—Beyond crop row following. J Field Robot. 2021;38(3):429–51.
+
[6] Chen C., Xiao Z., Zhang W., Wang Y., Zhu H. Effect of laser jump speed on temperature distribution and thermal stress in laser powder bed fusion. Opt. Laser Technol., 142, 107275, 2021.
  
−
[11] Thomasson JA, Baillie CP, Antille DL, Lobsey CR, McCarthy CL. Autonomous technologies in agricultural equipment: a review of the state of the art. Trans ASABE. 2019;62(1):1–17.
+
[7] Maity K.P., Choubey M. A review on vibration-assisted EDM, micro-EDM and WEDM. Surf. Rev. Lett., 26(5), 1830008, 2019.
  
−
[12] Tu X, Gai J, Tang L. Robust navigation control of a 4WD/4WS agricultural robotic vehicle. Comput Electron Agric. 2019;164:104892.
+
[8] Singh P., Singh L., Singh S. A review on magnetically assisted abrasive flow machining and abrasive material type. Proc. Inst. Mech. Eng. Part E J. Process Mech. Eng., 236:2765–2781, 2022.
  
−
[13] Bayar G, Bergerman M, Koku A B, Konukseven EI. Localization and control of an autonomous orchard vehicle. Comput Electron Agric. 2015;115:118–28.
+
[9] Zhou J., et al. Study on the mechanism of ultrasonic-assisted water confined laser micromachining of silicon. Opt. Lasers Eng., 132, 106118, 2020.
  
−
[14] Zaidner G, Shapiro A. A novel data fusion algorithm for low-cost localisation and navigation of autonomous vineyard sprayer robots. Biosyst Eng. 2016;146:133–48.
+
[10] Sun C., et al. Study on the effect of electrolytes on processing efficiency and accuracy of titanium alloy utilizing laser and shaped tube electrochemical machining. Materials, 17(3):689, 2024.
  
−
[15] Linz A, Brunner D, Fehrmann J, Herlitzius T, Keicher R, Ruckelshausen A, Schwarz H P. Modelling environment for an electrical driven selective sprayer robot in orchards. Adv Anim Biosci. 2017;8(2):848–53.
+
[11] Garcia S.M., Ramos J., Lamikiz A., Figueras J. Influence of process parameters in laser piercing. Appl. Sci., 9(16), 3231, 2019.
  
−
[16] Reina G, Milella A, Rouveure R, Nielsen M, Worst R, Blas M R. Ambient awareness for agricultural robotic vehicles. Biosyst Eng. 2016;146:114–32.
+
[12] Lu D., Liu Z., Wei X., Chen C., Wang D. Effect of post-processing methods on the surface quality of Ti6Al4V fabricated by laser powder bed fusion. Front. Mater., 10, 1126749, 2023.
  
−
[17] Andersen J C, Ravn O, Andersen N A. Autonomous rule-based robot navigation in orchards. IFAC Proc Vol. 2010;43(16):43–8.
+
[13] Deng T., Li J., Zheng Z., Tian W., Li G. Influence of plasma beam polishing process parameters on surface roughness of AISI 304 stainless steel. Appl. Surf. Sci., 585, 152741, 2022.
  
−
[18] Taylor K E. Summarizing multiple aspects of model performance in a single diagram. J Geophys Res Atmos. 2001;106(D7):7183–92.
+
[14] Zhong T., et al. Fabrication and characterization of silicon-based antimonene thin film via electron beam evaporation. Materials, 17(5), 1090, 2024.

Latest revision as of 04:39, 10 November 2025

Abstract

This research is aimed at Laser processing of micro holes there are recast layer and microcracks, analyzed the laser processing of recast layer formation mechanism and surface geometry features not, and for the laser processing of the formation of the recast layer in the process of analog simulation, for electrochemical finishing processing to remove the recast layer to provide a theoretical basis. The laser-electrolysis asynchronous composite processing experimental system was developed, and the electrolytic removal of recast layer on the wall of laser perforated holes and the process research of aperture trimming were carried out, which mainly analyzed the effects of electrolysis voltage, electrolyte and pulse electrolysis parameters on the rate of electrolysis and the effect of the removal of the recast layer. The cathode lifting method is also proposed to lift the tool cathode for orifice shaping after effective removal of the recast layer. The experimental results show that: when the current density is greater than 10.09 A/cm2, the electrolysis rate is proportional to the voltage; when the constant voltage electrolysis, the mixed solution of NaNO3 and NaCl enhances the effect of the recast layer removal significantly, and relative to the single solution with the same electrical conductivity, the value of the change in the surface roughness of the workpiece before and after the finishing process is enhanced more significantly, and there is no significant difference in the processing efficiency; the low-frequency wide pulse and high-frequency narrow pulse in the pulse electrolysis processing is favorable for the removal of recast layer. Pulse, high-frequency narrow pulse is conducive to the improvement of electrolysis rate, and the frequency of 1 kHz, the duty cycle of 40% to 60% of the electrolysis rate is the largest; at the same time, the use of cathodic enhancement method of aperture trimming processing, the use of the truncation effect, through the appropriate electrolytic processing parameters, to achieve the complete removal of the laser hole hole wall recast layer at the same time to complete the aperture trimming processing, to meet the demand for the use of performance of the small holes to further enhance the processing efficiency and small holes, and to improve the processing efficiency of the laser hole. Enhance the processing efficiency and functionality of small holes.

Keywords: Laser processing, recast layer simulation, electrochemical finishing, cathodic lift

1. Introduction

In the field of modern machinery and equipment, the application of microporous in enhancing the use of equipment performance and reliability and other aspects of the value is increasingly apparent. For example, in the key high-temperature components of aircraft engines, the application of microporous promotes the development of air film cooling technology, and effectively make up for the limitations of high-temperature-resistant materials to enhance the reliability and durability of the engine; in the field of internal combustion engines, the application of microporous design of injector nozzles not only significantly improves the effect of fuel atomization, but also plays an important role in improving combustion efficiency and effectively reducing harmful emissions. Therefore, the application of microporous not only promotes the development of greening technology, but also promotes the innovation of microporous machining technology and process, which makes the special machining technology such as electric discharge technology (EDM) [1], electrochemical machining (ECM) [2], and laser machining (LM) [3] become the mainstream microporous machining methods.

However, micro-hole machining technology based on special machining methods such as EDM, laser machining and electron beam is also facing some technical challenges. Due to the existence of the recast layer, the changes in its composition, structure, hardness and strength affect the performance of micro-holes in use, so scholars at home and abroad have carried out a wide range of white research in the removal of the recast layer and its effects. On the one hand, some scholars have deeply studied the formation mechanism of the recast layer, and while revealing the physical and chemical processes of the formation of the recast layer, they have also proposed the introduction of new processing media (e.g., nano-fluid, carnauba oil, etc.) [4,5] to adjust the processing environment [6,7] (e.g., temperature, pressure, etc.) and the development of new machining tools [8,9] and other means, which have effectively reduced the thickness of the recast layer; on the other hand, some scholars have reduced the formation and thickness of the recast layer by optimizing the process parameters [10,11] (e.g., current, voltage, and processing speed, etc.); in addition, some scholars have utilized post-processing techniques (e.g., chemical etching [12], ion-beam polishing [13], and electron-beam evaporation [14], as well as femtosecond laser technology, etc.) to achieve efficient removal of the recast layer and improve the microporosity. efficient removal and improved processing quality of micro-holes.

Despite this, some major problems remain. The formation of recast layers involves complex physical and chemical processes, including melting, solidification, and phase transformation of the material. These processes are influenced by a variety of factors, such as processing temperature, pressure, material composition etc. Their complexity makes it difficult in controlling the formation of recast layers. During micro-hole machining, the optimization of machining parameters is crucial to reduce the recast layer. However, finding the best combination of parameters is a challenging task due to the diversity of machining parameters and the coupling of interactions. In addition, the optimal parameters may be different for different materials and machining conditions, which further increases the difficulty of parameter optimization. Limitations of post-processing technologies: chemical etching may introduce new surface defects or contaminants, while ion and electron beams may be limited by equipment cost and operability, resulting in restricted form geometry of the processed object. The problem of the balance between processing efficiency and quality. In the process of micro-hole machining, there is a certain contradiction between improving the processing efficiency and guaranteeing the processing quality, in order to reduce the formation of recast layer, it may be necessary to reduce the processing speed or processing steps, but this will sacrifice the processing efficiency. Therefore, based on the characteristics of electrochemical light finishing processing, this paper proposes the concept of using electrochemical anodic dissolution to remove the recast layer, and the process method of electrochemical removal of recast layer is studied. Finally, a two-step lifting process method is proposed to complete the micro-hole orifice trimming processing on the basis of satisfying the high quality removal of the recast layer, so that it can meet the specific use performance requirements.

2. Experimental programming

2.1 Formation mechanism and simulation of recast layer and its surface geometric characteristics

2.1.1 Formation mechanism and simulation of recast layer

Laser processing is the result of the superposition of multiple single molten pools, so the recast layer formed by laser processing is inextricably linked to the formation of the single molten pool recast layer, the basic process of which is shown in Figure 1(a). The material under a single pulsed laser irradiation is rapidly heated to the melting and boiling points, and melting and vaporization occur, forming a solid, liquid, and vapor three-phase coexistence. The melt flows along the walls of the processed area under a combination of vaporizing pressure and thermal influences, resulting in the formation of a concave contour of the melt pool that resembles a replica of the laser energy distribution curve. At the end of a single laser pulse, the vaporized metal in the center of the melt pool releases a large amount of thermal energy, which causes the melt attached to the walls of the melt pool and the curved melt at the bottom to be subjected to the recoil pressure of the metal vapor jet directly, which leads to the splashing of melt in the melt pool. Among them, part of the melt splashes out of the melt pool to form melt spatter, and accumulates at the edge of the melt pool to form a flying edge or burr, the simulation results are shown in Figure 1(b); the other part of the melt will be deposited and attached to the surface of the inner wall of the melt pool,, and under the action of the combined coupling force, the melt will flow downward along the wall surface and reach a static equilibrium to form a smooth and excessive linear melt. After rapid cooling, the surface of the single molten pool forms a recast layer covered by a fused cladding after being subjected to a pressure gradient and a temperature gradient. The final laser process consists of the superposition of individual melt pools in the axial direction of the processing area and the formation of a recast layer with a periodic stream-like distribution on the surface of the hole wall.
Draft Seryazdan 636830651-image1.png
Figure 1. Schematic diagram of the simulation of recast layer formation

2.1.2 Surface geometry of the recast layer

As shown in Figure 2(a), at the surface of the initial melt pool, due to the large temperature gradient, the overflowed melt is mainly subject to Marangoni force, surface tension and gravity. The Marangoni force affects the flow of the melt, thus forming the shape of a domed dome; the surface tension and gravity in turn cause the overflowed melt to shrink outside the hole to form a ring-shaped accumulation.

As can be seen in Figure 2(b) below, in the upper part of the inner wall of the micro-hole, the recast layer has a smooth surface and relatively low thickness but is unevenly distributed along the periphery of the hole. Because the steam action is the strongest here, the melt pool is shallow, the metal vapor expansion rate is unevenly distributed, and a large amount of molten metal is randomly discharged, but under the action of the Marangoni force, it shows a smooth and excessive gully shape. In the 1/3 position from the top of the orifice, the recast layer surface formed a turbulent ripple-like undulation, randomly distributed in the circumferential direction, the thickness of a relative increase in the molten metal was a localized layer accumulation. Because with the non-stop stacking of the molten pool, the pressure gradient and the molten liquid velocity increase, so that the molten liquid layer of the explosion, the small size of the fast particles and the large size of the liquid particles with small velocity successively excluded by spattering, the vapor flow still has a high recoil force but weakened in relation to the orifice. In the middle and lower part of the micro-hole, the flow on the surface of the recast layer tends to stabilize, and the flow direction is more consistent, but the thickness reaches the maximum; at the same time, the layer spacing decreases, and a large number of overlapping melts blown down by the gas stream appear in the cross-section. Because here the melt pool flow rate has been lower, the melt by gravity and surface tension to reach equilibrium, the formation of a large number of droplets of solute accumulation, and at the same time because of the convection of the melt pool so that the melt can not be quickly discharged and thus re-melting and condensation to form a thicker recast layer. At the bottom of the micro-hole, the surface of the recast layer shows an obvious insufficient flow, because the steam effect here is weakened, and the melt sputtering becomes the main mode of discharge to increase the viscosity of the melt, which leads to the formation of localized agglomerates. Overall, the surface geometry of the laser-processed recast layer shows a stable and continuous periodic stripe distribution, which is characterized by an orderly wave-like microstructure on the macroscopic level and a spherical dome distribution of "peaks and valleys" on the microscopic level.
Draft Seryazdan 636830651-image2.png
Figure 2. Simulation of surface geometric features of recast layer with SEM

2.2 Design of experimental platforms

Experimentally used electrolytic combination processing device shown in Figure 3, the device has electrochemical processing module and three-coordinate displacement platform, the platform is equipped with three axes, three-axis linkage can be realized. -axis is equipped with electrochemical machining device, motion platform is equipped with a work box, electrochemical removal processing in the work box. The working box is made of plexiglass and resin materials, which not only realizes the electrical insulation from the machine tool, but also facilitates the observation of the experimental process.
Draft Seryazdan 636830651-picture- 1.svg
Figure 3. Electrochemical light finishing processing experimental platform

2.3 Design of experimental methodology

2.3.1 Experimental flow design and preparation of samples

The basic idea of the experiment, the laser was first used to process the prefabricated holes in the 2 mm thick metal plate, and then electrochemical processing was used to remove the recast layer on the hole wall, the specific process is shown in Figure 4. Laser parameters for the optimized parameters: pulse width of 0.2ms, peak power of 16kW, repetition frequency of 70Hz, drilling process along the laser head sprayed 0.6MPa argon to accelerate the exclusion of molten material, to reduce the burr, melt spattering and residual in the hole wall of the recast layer. Electrochemical processing, the use of motion control systems to insert the electrode wire centered in the pre-fabricated holes, detect whether the short circuit and set the pulse power parameters. First turn on the electrolyte pump, wait for the electrolyte to flow evenly through the hole and see a clear and stable liquid column at the exit, turn on the pulse power supply to start electrolysis, observe the experimental phenomena and power supply parameter changes, and turn off the power supply according to the set electrolysis time. The electrolyte is a neutral solution configured with pure water, and the dynamic liquid flushing method is used. In the experiment, considering the experimental error, 3 holes were processed under each parameter, and after the completion of the processing, the samples were cleaned, polished and metallurgically corroded, and the micro-hole morphology was observed with a scanning electron microscope, and the pore diameter was observed and measured with an optical microscope, and the average value of the 3 holes' diameters was finally taken under the same parameter. The micro-hole morphology of the sample is shown in Figure 5.
Draft Seryazdan 636830651-image5-c.png
Figure 4. Micro-hole machining process flowchart
Draft Seryazdan 636830651-image6.png
Figure 5. Laser processing sample drawing

2.3.2 Determination of electrochemical processing method

In the electrochemical machining process, generally keep the processing current or processing voltage constant, with the increase of workpiece aperture, the electrolyte resistance increases gradually. When the current is constant, the voltage increases with the increase of the electrolyte resistance, and the current density decreases with the increase of the processed surface area when; when the voltage is constant, the current decreases with the increase of the electrolyte resistance, and the current density decreases rapidly with the decrease of the current and the increase of the processed surface area. In summary, it can be found that, when the voltage is constant, the decreasing trend of current density is greater than that of constant current, which is conducive to ensuring the processing efficiency in the early stage while ensuring the surface quality in the later stage of processing, so this paper adopts constant voltage for electrolytic processing.

2.3.3 Selection of electrolyte in electrochemical processing

Electrolytic processing, the electrode potential applied at the interface between the workpiece and the solution is different, the workpiece processing surface is in a different state, NaNO3 solution is a passive electrolyte, the polarization curve of the anode of the workpiece into a non-linear distribution, passivation area of the metal surface to form an adsorbed oxygen layer or an oxide layer, i.e., passivation film; and precipitation of the oxygen area of the workpiece and the interface of the solution at the OH- ions easy to oxidize, precipitation of oxygen, precipitation of O2 easy to oxidation Metal surface, so that the workpiece processing surface at the passivation film becomes thicker. The passivation film is less conductive, which in turn reduces the processing current density and lowers the dissolution rate of the metal. The NaCl solution is an active electrolyte, and the polarization curve of the anode of the workpiece is linearly distributed. The activation capacity of Cl- in the solution is very strong, the anode surface in a variety of conditions are in the active state of low-value dissolution, does not produce passivation and its side reactions, so the metal dissolution rate is higher, but at the same time there is a serious stray corrosion, which seriously affects the machining accuracy. In order to improve the nonlinear dissolution characteristics of the electrolyte, improve the current efficiency, soften the passivation salt film, this paper adopts a certain concentration of NaNO3 solution mixed with a certain proportion of NaCl solution, in order to improve the machining efficiency at the same time easier to achieve the uneven dissolution or uneven super-passivation of the dissolution state, so as to improve the machining quality of the workpiece.

3. Results and analysis of removal of recast layer and orifice reshaping based on electrochemical light leveling

3.1 Effect of electrolysis parameters on the removal of recast layers

When constant voltage electrolysis is used, the appropriate voltage should be selected. Theoretically, when the electrolysis voltage increases, the amount of electricity passing through the surface increases and the electrolysis rate increases. The electrolysis products and heat in the processing gap also increase, increasing the flow resistance in the gap, resulting in a decrease in the flow of electrolyte, so that the ability to exclude electrolysis products and heat is reduced. When there is a serious imbalance between the two, abnormal phenomena such as evaporation, boiling, and cavitation will occur in the processing gap, leading to serious failures such as short circuits and scarring, resulting in the interruption of processing. In addition, with the increase in current density, the electric field strength around the electrode wire increases, the stray corrosion around the orifice is enhanced, and the orifice is not rounded after electrolysis. Therefore, the voltage increase should not destroy the above balance as a prerequisite for the given electrolytic processing conditions, need to choose a suitable voltage value. Take the electrolysis time of 30s, the electrolyte is the conductivity of 100.4ms/cm NaNO3 and NaCl mixed solution solution, respectively, with a voltage of 3-18V (interval 3V) for the recast layer removal experiment.

After the completion of the experiment, the experimental results are processed: take the amount of hole expansion after processing and surface roughness change value as the reference amount; different voltage electrolysis, the expansion of the hole diameter is different, take the median value of the hole diameter in the process of electrolysis (with the minimum voltage electrolysis hole median value) as the benchmark, and take the change in the quality of the processing before and after the processing as an auxiliary reference for processing rate.

From the Figure 6, it can be seen that after the same time of electrolysis, the pore radius and electrolysis rate increased with the increase of electrolysis voltage. When the voltage is 15V, the recast layer is completely removed. At this time, the electrolysis current is 0.5 A. Calculation gives a minimum current density of 10.09 A/cm2. The mass change and pore radius change shown in Figure 6 reflect that the electrolysis rate is approximately proportional to the voltage. When electrolysis removes the recast layer, the volume electrochemical equivalent of the material is a constant value, and the oxidation reaction of Ni, Fe, Cr, and other elements in the material occurs, in which Ni, Fe, and Cr will be oxidized with multiple valences according to the current density, and when the current density is greater than, all three elements are oxidized to the cation with the highest valence, i.e., the current efficiency is constant. When the electrolysis voltage is 6 V, the extension of the fitted primary curve can be found that the electrolysis rate is larger at this time. This is because when the current density is small, Ni, Fe, Cr elements are partially oxidized to low valence cations, at this time the current efficiency is larger, and the proportion of high valence oxidation of these three elements increases with the increase of current density, that is, the current efficiency decreases with the increase of current density.
Draft Seryazdan 636830651-image9.png
Figure 6. Plot of the effect of voltage parameters on the removal of recast layer processing
Figure 7 shows the SEM and metallographic images of the control holes and after removal of the recast layer by light-needle processing, from which it can be seen that the holes are rounded after light-finishing processing, and the recast layer is completely removed and the hole wall is smooth. When the constant pressure finishing process, the higher the voltage, the higher the current density, the higher the electrolysis rate. But at the same time as the voltage increases due to the hole entrance surface near the tool cathode, the electric field effect than other parts of the General Assembly serious stray corrosion, and because the entrance surface to increase the auxiliary anode, and by providing a potential difference to change the direction of the electric field of the anode entrance surface to reduce the entrance of the stray corrosion, effective control of electrochemical reaction of the hole entrance near the upper surface of the hole inlet, practical electrolytic machining, generally according to the cut-off In actual electrolytic processing, the voltage is generally determined according to the cut-off voltage and the electrolytic processing area. Under the condition of ensuring the processing surface quality, the electrolytic voltage can be increased in order to obtain a higher electrolytic rate, and the electrolyte flow rate can be increased at the same time in order to meet the exclusion of electrolytic processing products and heat.
Draft Seryazdan 636830651-image10.png
Figure 7. SEM and metallographic images after removal of the recast layer

3.2 Effect of pulsed power supply on the removal of recast layers

The traditional DC electrolytic machining has a strong ability to scatter etching and a weak ability to centralized etching, which affects the accuracy of electrolytic machining, the general three-dimensional surface molding accuracy of 0.2 to 0.5 mm, and the hole machining molding accuracy of 0.025 to 0.05 mm. High-frequency, narrow pulse electrolytic machining can achieve high precision (dimensional accuracy less than 5m, surface roughness less than 0.03mm), small gap (10 to 50m) machining, machining quality is greatly improved. The principle of pulse electrolytic processing is to replace the continuous DC power supply with periodic intermittent power supply, and the anode undergoes periodic intermittent dissolution in the electrolyte. It uses the intermittent depolarization of the pulse gap with power failure to dissipate heat from the workpiece, and the electrochemical properties, flow field, and electric field of the machining gap are restored to the starting state. Pulse current electrolysis, the gap produces hydrogen pressure wave synchronized with the pulse current, the frequency and intensity with the increase of pulse frequency and enhancement, which strengthens the stirring effect on the electrolyte, so that the flow field distribution in the gap tends to be uniform, and to improve the heat dissipation conditions in the gap, so as to make the minimum stable machining gap is greatly reduced, and thus to enhance the fixed-domain nature of electrolytic machining. Therefore, this paper compares the difference between the processing quality of pulse power supply and DC power supply, and finally chooses the processing method of pulse current electrolysis to get a higher electrolysis rate under the premise that the processing quality can be guaranteed.

As can be seen from Figure 8(a), the surface quality obtained after processing with DC as the processing power source is relatively rough, the recast layer is not completely removed, and the electrochemical dissolution effect is small, and because of the DC electrolytic processing scattering corrosion ability is strong, so that the stray corrosion area is larger and the corrosion effect is more obvious, and at the same time, due to the fact that by-products can't be eliminated in time during the DC processing and electrolytic solution can't be renewed in time, which makes the local resistance increase, resulting in the inner wall of the small holes in part of the recast layer was not removed. As can be seen from Figure 8(b), the use of pulsed current as the power supply processing after the surface is more smooth, the recast layer is completely removed and the processing quality is relatively stable, effectively solving the problems arising from the DC power supply, and further improving the quality and stability of the processing of electrolytic removal of the recast layer.
Draft Seryazdan 636830651-image11.png
Figure 8. Comparison chart of AC power supply and DC power supply

3.3 Influence of cathodic lifting method on orifice reshaping

In order to further improve the machining effect of micro small hole workpieces, a staged combination of processing methods is proposed, based on the electrolytic removal of the recast layer, in the same station to further complete the small hole electrolytic repair of the machining method, i.e., cathode lifting method. The method is as follows: in the first stage, the surface quality of the workpiece is rapidly improved and the surface roughness is reduced by relatively large voltage processing to ensure the rapid removal of the recast layer; in the second stage, after the completion of the removal of the recast layer, the electric field distribution is influenced by changing the electrode position and the relatively small voltage is used for the trimming process to obtain a better surface quality and to realize the goal of the trimming of the micro-hole aperture. Due to the use of hybrid electrolyte, as mentioned above, the electrolyte has the characteristic of cutting the gap, when using small voltage processing, this time the inner wall of the hole although the current through, but the anode does not dissolve, the current efficiency is 0, which has been processed to protect the wall of the hole at the same time as the hole inlet trimming the shape of the hole to make the micro-hole has a better to meet the demand for the performance of the use of the micro-hole. Based on the above research, the experimental process parameters are as follows: the electrolyte used is a mixed solution of NaNO3 and NaCl with a conductivity of 100.4ms/cm, the electrolysis voltage is 4v, and the electrolysis time is 20s.

From the Figure 9(a) can be seen, without improving the processing method workpiece due to the over-processing phase of the surface obtained on the more rough and micro-hole expansion obvious, poor machining locality, taper relative to the Figure 9(b) is greater, at the same time, the effect of repairing the shape of the micro-hole can not meet the demand for the use of the performance of the micro-hole is not obvious; from the Figure 9(b) can be seen, after the elevation of the method of low-pressure combination of machining, the inner wall of the hole in the cut off gap characteristics of the end of the end of the protection of the dissolution occurred, the machining of locality Higher, the height of the surface bulge is reduced, the surface of the workpiece becomes relatively flat, the taper relative to the Figure 9(a) has obvious improvement, while the effect of the repair effect is good, can meet the functional requirements of the micro-hole.
Draft Seryazdan 636830651-image12.png
Figure 9. Comparison of the results of the cathodic lift method

4. Conclusions

In this paper, the use of electrochemical finishing processing method to remove the heavy casting layer left on the hole wall by laser processing and at the same time complete the orifice trimming processing can better meet the demand of micro-hole performance. Theoretical analysis and simulation of the formation mechanism of the recast layer and the surface geometrical features during laser processing were carried out, and experiments were carried out for the removal of the recast layer and orifice shaping, and small holes with the recast layer completely removed and the orifice rounded were obtained. Based on the experimental results, the following conclusions were obtained:

1. Laser processing is made by a single molten pool superimposed in the axial direction of the processing area, the molten material remaining in the molten pool in the combined force coupling role in the formation of a smooth excess of linear melt, and in the rapid cooling of the single molten pool surface in the pressure gradient and the temperature gradient, the formation of a recast layer covered by the fusion layer. The surface geometry of the laser-processed recast layer shows a stable and continuous periodic stripe distribution, which is characterized by an ordered wave-like microstructure on the macro level and a spherical dome distribution of "peaks and valleys" on the micro level.

2. Current density is an important parameter affecting the electrolysis rate. When using mixed solution finishing processing recast layer, the current density is greater than 10.09A/cm2, the current efficiency remains unchanged, and the electrolysis rate is proportional to the electrolysis voltage. When the actual processing, the current density is too large easily lead to processing area scarring, short circuit and other quality defects. Therefore, according to the current density greater than 10.09A/cm2 and electrolytic processing area to determine the current voltage, according to the electrolyte flow rate to increase the voltage to obtain a higher efficiency of finishing processing.

3. When the electrolyte with the same conductivity is used under constant pressure processing conditions, the surface quality of the surface processed with the mixed electrolyte of NaNO3 and NaCl is good, and the recast layer is completely removed; while the surface processed with the electrolyte of NaCl is seriously corroded by stray corrosion, and the recast layer is not completely removed.

4. The pulse effect in pulse finishing, the passivation of the anode of the workpiece, the stirring effect of the hydrogen pressure wave and the maintenance of the stability of the flow and electric fields during the power-off gap play a key role in enhancing the surface quality of the finish after the removal of the recast layer by the finishing process.

5. When the cathodic lifting method is used to process the micro-hole, the truncation effect is utilized so that the inner wall surface of the micro-hole will not be processed twice while the orifice is trimmed to achieve the shape of the process, and ultimately the inner wall is smooth and the orifice is rounded to obtain a micro-hole with better usability.

Acknowledgements

This work was supported by Application of corrosion protection and online monitoring technology based on chlor-alkali industry (ZYYD2023B03).

References

[1] Han L., Sartin M.M., Tian Z.-Q., Zhan D., Tian Z.-W. Electrochemical nanomachining. Curr. Opin. Electrochem., 22:80–86, 2020.

[2] Sisodiya M.S., Shukla S., Bajpai V. Feasibility analysis of novel Maglev EDM by comparing with conventional micro EDM. Sci. Rep., 12, 2613, 2022.

[3] Schmidt M., et al. Advances in macro-scale laser processing. CIRP Ann., 67:719–742, 2018.

[4] Wang X., et al. Nanofluids application in machining: a comprehensive review. Int. J. Adv. Manuf. Technol., 131:3113–3164, 2024.

[5] Kozak J., Rozenek M., Dabrowski L. Study of electrical discharge machining using powder-suspended working media. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 217:1597-1602, 2003.

[6] Chen C., Xiao Z., Zhang W., Wang Y., Zhu H. Effect of laser jump speed on temperature distribution and thermal stress in laser powder bed fusion. Opt. Laser Technol., 142, 107275, 2021.

[7] Maity K.P., Choubey M. A review on vibration-assisted EDM, micro-EDM and WEDM. Surf. Rev. Lett., 26(5), 1830008, 2019.

[8] Singh P., Singh L., Singh S. A review on magnetically assisted abrasive flow machining and abrasive material type. Proc. Inst. Mech. Eng. Part E J. Process Mech. Eng., 236:2765–2781, 2022.

[9] Zhou J., et al. Study on the mechanism of ultrasonic-assisted water confined laser micromachining of silicon. Opt. Lasers Eng., 132, 106118, 2020.

[10] Sun C., et al. Study on the effect of electrolytes on processing efficiency and accuracy of titanium alloy utilizing laser and shaped tube electrochemical machining. Materials, 17(3):689, 2024.

[11] Garcia S.M., Ramos J., Lamikiz A., Figueras J. Influence of process parameters in laser piercing. Appl. Sci., 9(16), 3231, 2019.

[12] Lu D., Liu Z., Wei X., Chen C., Wang D. Effect of post-processing methods on the surface quality of Ti6Al4V fabricated by laser powder bed fusion. Front. Mater., 10, 1126749, 2023.

[13] Deng T., Li J., Zheng Z., Tian W., Li G. Influence of plasma beam polishing process parameters on surface roughness of AISI 304 stainless steel. Appl. Surf. Sci., 585, 152741, 2022.

[14] Zhong T., et al. Fabrication and characterization of silicon-based antimonene thin film via electron beam evaporation. Materials, 17(5), 1090, 2024.
Back to Top
GET EPUB

Document information

Published on 04/06/24
Accepted on 20/05/24
Submitted on 04/05/24

Volume 40, Issue 2, 2024
DOI: 10.23967/j.rimni.2024.05.008
Licence: CC BY-NC-SA license

Document Score

0

Views 596
Recommendations 0

Share this document

Keywords

• • •

claim authorship

Are you one of the authors of this document?

I am an author