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Effective Sampling and Distance Metrics for
3D Rigid Body Path Planning

James J. Kuffner, Jr.


The Robotics Institute
Carnegie Mellon University
5000 Forbes Ave., Pittsburgh, PA 15213, USA

Digital Human Research Center
National Institute of Advanced
Science and Technology (AIST)
2-41-6 Aomi, Koto-ku, Tokyo, Japan 135-0064


Important implementation issues in rigid body path planning are often overlooked. In particular, sampling-based motion planning algorithms typically require a distance metric defined on the configuration space, a sampling function, and a method for interpolating sampled points. The configuration space of a 3D rigid body is identified with the Lie group SE(3). Defining proper metrics, sampling, and interpolation techniques for SE(3) is not obvious, and can become a hidden source of failure for many planning algorithm implementations. This paper examines some of these issues and presents techniques which have been found to be effective experimentally for Rigid Body path planning.

1997 - 2006 © James Kuffner, Jr.