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As future personal vehicles start enjoying the ability to fly, tackling safe transportation coordination can be a tremendous task, far beyond the current challenge on radar screen monitoring of the already saturated air traffic control. Our focus is on the distributed safe-distance coordination among a group of autonomous flying vehicle agents, where each follows its own current straight-line direction in a 3D space with variable speeds. A virtual spring-based model is proposed for the group coordination. Within a specified neighborhood radius, each vehicle forms a virtual connection with each neighbor vehicle by a virtual spring. As the vehicle changes its position, speed and altitude, the total resultant forces on each virtual spring try to maintain zero by moving to the mechanical equilibrium point. The agents then add the simple total virtual spring constraints to their movements to determine their next positions individually. Together, the multi-agent vehicles reach a group behavior, where each of them keeps a minimal safe-distance with others. A new safe behavior thus arises in the group level. With the proposed virtual spring coordination model, the vehicles need no direct communication with each other, require only minimum local processing resources, and the control is completely distributed. New behaviors can now be formulated and studied based on the proposed model, e.g., how a fast driving vehicle can find its way though the crowd by avoiding the other vehicles effortlessly1. | As future personal vehicles start enjoying the ability to fly, tackling safe transportation coordination can be a tremendous task, far beyond the current challenge on radar screen monitoring of the already saturated air traffic control. Our focus is on the distributed safe-distance coordination among a group of autonomous flying vehicle agents, where each follows its own current straight-line direction in a 3D space with variable speeds. A virtual spring-based model is proposed for the group coordination. Within a specified neighborhood radius, each vehicle forms a virtual connection with each neighbor vehicle by a virtual spring. As the vehicle changes its position, speed and altitude, the total resultant forces on each virtual spring try to maintain zero by moving to the mechanical equilibrium point. The agents then add the simple total virtual spring constraints to their movements to determine their next positions individually. Together, the multi-agent vehicles reach a group behavior, where each of them keeps a minimal safe-distance with others. A new safe behavior thus arises in the group level. With the proposed virtual spring coordination model, the vehicles need no direct communication with each other, require only minimum local processing resources, and the control is completely distributed. New behaviors can now be formulated and studied based on the proposed model, e.g., how a fast driving vehicle can find its way though the crowd by avoiding the other vehicles effortlessly1. | ||
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* [http://necsi.edu/events/iccs7/papers/4a4c3ac3ee18ed6cd2149a2b7e62.pdf http://necsi.edu/events/iccs7/papers/4a4c3ac3ee18ed6cd2149a2b7e62.pdf] | * [http://necsi.edu/events/iccs7/papers/4a4c3ac3ee18ed6cd2149a2b7e62.pdf http://necsi.edu/events/iccs7/papers/4a4c3ac3ee18ed6cd2149a2b7e62.pdf] | ||
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| + | * [http://link.springer.com/content/pdf/10.1007/978-3-642-18003-3_4 http://link.springer.com/content/pdf/10.1007/978-3-642-18003-3_4], | ||
| + | : [http://dx.doi.org/10.1007/978-3-642-18003-3_4 http://dx.doi.org/10.1007/978-3-642-18003-3_4] | ||
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| + | * [https://link.springer.com/chapter/10.1007/978-3-642-18003-3_4 https://link.springer.com/chapter/10.1007/978-3-642-18003-3_4], | ||
| + | : [https://www.scipedia.com/public/Daneshvar_Shih_2012a https://www.scipedia.com/public/Daneshvar_Shih_2012a], | ||
| + | : [https://rd.springer.com/chapter/10.1007/978-3-642-18003-3_4 https://rd.springer.com/chapter/10.1007/978-3-642-18003-3_4], | ||
| + | : [https://necsi.edu/events/iccs7/papers/4a4c3ac3ee18ed6cd2149a2b7e62.pdf https://necsi.edu/events/iccs7/papers/4a4c3ac3ee18ed6cd2149a2b7e62.pdf], | ||
| + | : [https://academic.microsoft.com/#/detail/119945929 https://academic.microsoft.com/#/detail/119945929] | ||
Latest revision as of 16:31, 21 January 2021
Abstract
As future personal vehicles start enjoying the ability to fly, tackling safe transportation coordination can be a tremendous task, far beyond the current challenge on radar screen monitoring of the already saturated air traffic control. Our focus is on the distributed safe-distance coordination among a group of autonomous flying vehicle agents, where each follows its own current straight-line direction in a 3D space with variable speeds. A virtual spring-based model is proposed for the group coordination. Within a specified neighborhood radius, each vehicle forms a virtual connection with each neighbor vehicle by a virtual spring. As the vehicle changes its position, speed and altitude, the total resultant forces on each virtual spring try to maintain zero by moving to the mechanical equilibrium point. The agents then add the simple total virtual spring constraints to their movements to determine their next positions individually. Together, the multi-agent vehicles reach a group behavior, where each of them keeps a minimal safe-distance with others. A new safe behavior thus arises in the group level. With the proposed virtual spring coordination model, the vehicles need no direct communication with each other, require only minimum local processing resources, and the control is completely distributed. New behaviors can now be formulated and studied based on the proposed model, e.g., how a fast driving vehicle can find its way though the crowd by avoiding the other vehicles effortlessly1.
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Published on 01/01/2012
Volume 2012, 2012
DOI: 10.1007/978-3-642-18003-3_4
Licence: CC BY-NC-SA license
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