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		<updated>2026-04-21T17:47:54Z</updated>
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		<title>Scipediacontent: Scipediacontent moved page Draft Content 110117667 to Han et al 2019a</title>
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				<updated>2021-02-02T05:46:48Z</updated>
		
		<summary type="html">&lt;p&gt;Scipediacontent moved page &lt;a href=&quot;/public/Draft_Content_110117667&quot; class=&quot;mw-redirect&quot; title=&quot;Draft Content 110117667&quot;&gt;Draft Content 110117667&lt;/a&gt; to &lt;a href=&quot;/public/Han_et_al_2019a&quot; title=&quot;Han et al 2019a&quot;&gt;Han et al 2019a&lt;/a&gt;&lt;/p&gt;
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				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;Revision as of 05:46, 2 February 2021&lt;/td&gt;
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		<author><name>Scipediacontent</name></author>	</entry>

	<entry>
		<id>https://www.scipedia.com/wd/index.php?title=Han_et_al_2019a&amp;diff=202389&amp;oldid=prev</id>
		<title>Scipediacontent: Created page with &quot; == Abstract ==  We study the labeled multi-robot path planning problem in continuous 2D and 3D domains in the absence of obstacles where robots must not collide with each oth...&quot;</title>
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				<updated>2021-02-02T05:46:42Z</updated>
		
		<summary type="html">&lt;p&gt;Created page with &amp;quot; == Abstract ==  We study the labeled multi-robot path planning problem in continuous 2D and 3D domains in the absence of obstacles where robots must not collide with each oth...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
We study the labeled multi-robot path planning problem in continuous 2D and 3D domains in the absence of obstacles where robots must not collide with each other. For an arbitrary number of robots in arbitrary initial and goal arrangements, we derive a polynomial time, complete algorithm that produces solutions with constant-factor optimality guarantees on both makespan and distance optimality, in expectation, under the assumption that the robot labels are uniformly randomly distributed. Our algorithm only requires a small constant-factor expansion of the initial and goal configuration footprints for solving the problem, i.e., the problem can be solved in a fairly small bounded region. Beside theoretical guarantees, we present a thorough computational evaluation of the proposed solution. In addition to the baseline implementation, adapting an effective (but non-polynomial time) routing subroutine, we also provide a highly efficient implementation that quickly computes near-optimal solutions. Hardware experiments on the microMVP platform composed of non-holonomic robots confirms the practical applicability of our algorithmic pipeline.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Original document ==&lt;br /&gt;
&lt;br /&gt;
The different versions of the original document can be found in:&lt;br /&gt;
&lt;br /&gt;
* [http://arxiv.org/pdf/1709.08215 http://arxiv.org/pdf/1709.08215]&lt;br /&gt;
&lt;br /&gt;
* [http://xplorestaging.ieee.org/ielx7/8574473/8593358/08594417.pdf?arnumber=8594417 http://xplorestaging.ieee.org/ielx7/8574473/8593358/08594417.pdf?arnumber=8594417],&lt;br /&gt;
: [http://dx.doi.org/10.1109/iros.2018.8594417 http://dx.doi.org/10.1109/iros.2018.8594417]&lt;br /&gt;
&lt;br /&gt;
* [https://dblp.uni-trier.de/db/conf/iros/iros2018.html#HanRY18 https://dblp.uni-trier.de/db/conf/iros/iros2018.html#HanRY18],&lt;br /&gt;
: [https://academic.microsoft.com/#/detail/2795484789 https://academic.microsoft.com/#/detail/2795484789]&lt;/div&gt;</summary>
		<author><name>Scipediacontent</name></author>	</entry>

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