Improved Heuristic Search for Sparse Motion Planning Data Structures

Proceedings of the International Symposium on Combinatorial Search, 7

Volume

Vol. 7 No. 1 (2014): Seventh Annual Symposium on Combinatorial Search

Research Abstracts

Sampling-based methods provide efficient, flexible solutions for motion planning, even for complex, high-dimensional systems. Asymptotically optimal planners ensure convergence to the optimal solution, but produce dense structures. This work shows how to extend sparse methods achieving asymptotic near-optimality using multiple-goal heuristic search during graph constuction. The resulting method produces identical output to the existing Incremental Roadmap Spanner approach but in an order of magnitude less time.

10.1609/socs.v5i1.18334