Probabilistic path planning with extended local planners
Abstract
We present a path planning algorithm for a six-degree-of-freedom (6 DOF) polyhedral robot moving in a known and static environment. The planner is the dual-tree rapidly exploring random tree (RRT) algorithm that uses a novel local planner. A local planner is a subroutine that determines whether two robot configurations can be connected by a simple path. The local planner we develop searches a 2 DOF or a 3 DOF subspace of the configuration space, whereas prior planners search the line segment that connects the two configurations. Although our planner has a higher cost at the local planning level, the empirical data shows that our planner outperforms prior planners on problems with narrow channels and performs comparably on other problems.
Degree
Ph.D.
Advisors
Sacks, Purdue University.
Subject Area
Robotics|Computer science
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