Manipulation planning on constraint manifolds

Authors:
Dmitry Berenson;Siddhartha S. Srinivasa;Dave Ferguson;James J. Kuffner
Affiliations:
The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA;The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA and Intel Research Pittsburgh, Pittsburgh, PA;The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA and Intel Research Pittsburgh, Pittsburgh, PA;The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

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Abstract

We present the Constrained Bi-directional Rapidly-Exploring Random Tree (CBiRRT) algorithm for planning paths in configuration spaces with multiple constraints. This algorithm provides a general framework for handling a variety of constraints in manipulation planning including torque limits, constraints on the pose of an object held by a robot, and constraints for following workspace surfaces. CBiRRT extends the Bi-directional RRT (BiRRT) algorithm by using projection techniques to explore the configuration space manifolds that correspond to constraints and to find bridges between them. Consequently, CBiRRT can solve many problems that the BiRRT cannot, and only requires one additional parameter: the allowable error for meeting a constraint. We demonstrate the CBiRRT on a 7DOF WAM arm with a 4DOF Barrett hand on a mobile base. The planner allows this robot to perform household tasks, solve puzzles, and lift heavy objects.