Abstract
Mobile robots often find themselves in a situation where they must find a trajectory to another position in their environment, subject to constraints posed by obstacles and the robot’s capabilities. This poses the problem of planning a path through a continuous domain. Several approaches have been used to address this problem each with some limitations, including state discretizations, planning efficiency, and lack of interleaved execution. Rapidly-exploring random trees (RRTs) are a recently developed algorithm on which fast continuous domain path planners can be based. In this work, we build a path planning system based on RRTs that interleaves planning and execution, first evaluating it in simulation and then applying it to physical robots. Our algorithm, ERRT (execution extended RRT), introduces two novel extensions of previous RRT work, the waypoint cache and adaptive cost search, which improve replanning efficiency and the quality of generated paths. ERRT is successfully applied to a multi-robot system. Results demonstrate that ERRT is improves efficiency and performs competitively with existing heuristic and reactive real-time path planning approaches. ERRT has shown to offer a major step with great potential for path planning in challenging continuous, highly dynamic domains.
This research was sponsored by Grants Nos. DABT63-99-1-0013, F30602-98-2-0135 and F30602-97-2-0250. The information in this publication does not necessarily reflect the position of the funding agencies and no official endorsement should be inferred.
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© 2003 Springer-Verlag Berlin Heidelberg
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Bruce, J., Veloso, M.M. (2003). Real-Time Randomized Path Planning for Robot Navigation. In: Kaminka, G.A., Lima, P.U., Rojas, R. (eds) RoboCup 2002: Robot Soccer World Cup VI. RoboCup 2002. Lecture Notes in Computer Science(), vol 2752. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45135-8_23
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DOI: https://doi.org/10.1007/978-3-540-45135-8_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40666-2
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