Authors: Nancy M. Amato, O. Burchan Bayazit, Lucia K. Dale, Christopher Jones, Daniel Vallejo

Venue: Proceedings of IEEE International Conference on Robotics and Automation
DOI: 10.1109/ROBOT.1998.677043
Link to Publication

Abstract:
This paper presents a comparative evaluation of different distance metrics and local planners within the content of probabilistic roadmap methods for motion planning. Both C-space and workspace distance metrics and local planners are considered. The study concentrates on cluttered 3D workspaces, typical of mechanical designs. Our results include recommendations for selecting appropriate combinations of distance metrics and local planners for use in motion planning methods, particularly probabilistic roadmap methods. We find that each local planner makes some connections than none of the others do indicating that better connected roadmaps will be constructed using multiple local planners. We propose a new local planning method, we call rotate-at-s, that outperforms the common straight-line in C-space method in crowded environments. 

@inproceedings{Amato-cgdmal-1998, 
 author = {Amato, N.M. and Bayazit, O.B. and Dale, L.K. and Jones, C. and Vallejo, D.}, 
 booktitle = {Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146)}, 
 doi = {10.1109/ROBOT.1998.677043}, 
 number = {}, 
 pages = {630-637 vol.1}, 
 title = {Choosing good distance metrics and local planners for probabilistic roadmap methods}, 
 volume = {1}, 
 year = {1998} 
}