vPlan: A Voronoi-Based Hybrid Motion Planner

Mark Foskey, Maxim Garber, Ming C. Lin, Dinesh Manocha

Abstract

We present a hybrid path planning algorithm for rigid and articulated bodies translating and rotating in a 3D workspace. Our approach generates a Voronoi roadmap in the workspace and combines it with ``bridges'' computed by a randomized path planner with Voronoi-biased sampling. The Voronoi roadmap is computed from a discrete approximation to the generalized Voronoi diagram (GVD) of the workspace, which is generated using graphics hardware. By this use of the GVD, portions of the path can be generated without random sampling, substantially reducing the number of random samples needed for the full query. The planner has been implemented and tested on a number of benchmarks. Some preliminary comparisons with a randomized motion planner indicate that our planner performs more than an order of magnitude faster in several challenging scenarios.

Publications

A Voronoi-Based Hybrid Motion Planner
Mark Foskey, Maxim Garber, Ming Lin, and Dinesh Manocha

Proc. IEEE/RSJ International Conf. on Intelligent Robots and Systems, 2001: pdf(356k)
UNC Chapel Hill Computer Science Technical Report TR00-025, 2000: pdf(245k)

Example Path Videos

Piano
Winding Tunnel
2D Maze
Articulated robot in a 2D maze
3D Maze
Walls with holes
Pegs


For More information visit the Univerisity of North Carolina web pages on Motion Planning, and vPlan


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