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arXiv · 1906.03239

Multitasking collision-free motion planning algorithms in Euclidean spaces

Cesar A. Ipanaque Zapata·Jesus Gonzalez
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Abstract

We present optimal motion planning algorithms which can be used in designing practical systems controlling objects moving in Euclidean space without collisions. Our algorithms are optimal in a very concrete sense, namely, they have the minimal possible number of local planners. Our algorithms are motivated by those presented by Mas-Ku and Torres-Giese (as streamlined by Farber), and are developed within the more general context of the multitasking (a.k.a.~higher) motion planning problem. In addition, an eventual implementation of our algorithms is expected to work more efficiently than previous ones when applied to systems with a large number of moving objects.

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Cesar A. Ipanaque Zapata, Jesus Gonzalez. 2021-01-24. Multitasking collision-free motion planning algorithms in Euclidean spaces. https://doi.org/10.1142/s1793830920500408

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