This paper presents a motion planning algorithm capable of exploiting the experience gained in previous path computations in the same static workspace. The algorithm takes advantage of a parallel approach to speed up computation and compile a graph retaining useful knowledge about the environment. Experimental results assess the performance improvement of the experience-based planner over the parallel implementation of a well-known probabilistic motion planning algorithm.
ERPP: an experience-based randomized path planner
REGGIANI, MONICA
2000
Abstract
This paper presents a motion planning algorithm capable of exploiting the experience gained in previous path computations in the same static workspace. The algorithm takes advantage of a parallel approach to speed up computation and compile a graph retaining useful knowledge about the environment. Experimental results assess the performance improvement of the experience-based planner over the parallel implementation of a well-known probabilistic motion planning algorithm.
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