Effective sampling and distance metrics for 3D rigid body path planning

被引:141
作者
Kuffner, JJ [1 ]
机构
[1] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA
来源
2004 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1- 5, PROCEEDINGS | 2004年
关键词
D O I
10.1109/ROBOT.2004.1308895
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Important implementation issues in rigid body path planning are often overlooked. In particulars 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 or 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.
引用
收藏
页码:3993 / 3998
页数:6
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