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.
IEEE International Conference on Robotics and Automation, ICRA 2000
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/179233
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