Abstract
We present a novel method for robot motion planning that constructs a network of collision free paths using a randomized search over a potential field in Configuration Space. Our method finds local minima and then connects them to form a graph, which we call a roadmap. We use a gradient search scheme to find the local minima very efficiently and accurately. To find a path between two configurations, it is then a simple matter to connect given start and goal configurations to the roadmap and to use a standard graph search algorithm to search the roadmap. The construction of the roadmap can be done in parallel with very little communication.
This research was partially supported by NSF grants CCR-9405380 and CCR9628786.
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© 1998 Springer-Verlag Berlin Heidelberg
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Kim, SW., Boley, D. (1998). Analytical potential fields and control strategies for motion planning. In: Pasqual del Pobil, A., Mira, J., Ali, M. (eds) Tasks and Methods in Applied Artificial Intelligence. IEA/AIE 1998. Lecture Notes in Computer Science, vol 1416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64574-8_394
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DOI: https://doi.org/10.1007/3-540-64574-8_394
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