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Fast Motion Planning by Parallel Processing – a Review

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Abstract

One of the many features needed to support the activities of autonomoussystems is the ability to plan motion. This enables robots to move in theirenvironment securely and to accomplish given tasks. Unfortunately, thecontrol loop comprising sensing, planning, and acting has not yet beenclosed for robots in dynamic environments. One reason involves the longexecution times of the motion planning component. A solution for thisproblem is offered by the use of highly parallel computation. Thus, animportant task is the parallelization of existing motion planning algorithmsfor robots so that they are suitable for highly parallel computation. Inseveral cases, completely new algorithms have to be designed, so that aparallelization is feasible. In this survey, we review recent approaches tomotion planning using parallel computation. As a classification scheme, weuse the structure given by the different approaches to the robot’smotion planning. For each approach, the available parallel processingmethods are discussed. Each approach is assigned a unique class. Finally,for each research work referenced, a list of keywords is given.

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ReferencesA list of keywords is given for each reference. As far as possible, at least one keyword is chosen from each orthogonal keyword group. The keywords have the same order as in Table 1. As additional keywords, we use introductionand survey

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    Dominik Henrich

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Henrich, D. Fast Motion Planning by Parallel Processing – a Review. Journal of Intelligent and Robotic Systems 20, 45–69 (1997). https://doi.org/10.1023/A:1007948727999

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