Date of Original Version

5-2010

Type

Conference Proceeding

Abstract or Description

We present a proof for the probabilistic completeness of RRT-based algorithms when planning with constraints on end-effector pose. Pose constraints can induce lower-dimensional constraint manifolds in the configuration space of the robot, making rejection sampling techniques infeasible. RRT-based algorithms can overcome this problem by using the sample-project method: sampling coupled with a projection operator to move configuration space samples onto the constraint manifold. Until now it was not known whether the sample-project method produces adequate coverage of the constraint manifold to guarantee probabilistic completeness. The proof presented in this paper guarantees probabilistic completeness for a class of RRT-based algorithms given an appropriate projection operator. This proof is valid for constraint manifolds of any fixed dimensionality.

DOI

10.1109/ROBOT.2010.5509694

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Robotics Commons

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Published In

Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) , 2724-2730.