Authors: N.M. Amato, L.K. Dale

Venue: Proceedings of IEEE International Conference on Robotics and Automation
DOI: 10.1109/ROBOT.1999.770055
Link to Publication

Abstract:
In this paper we report on our experience in parallelizing probabilistic roadmap motion planning methods (PRMs). We show that significant, scalable speed-ups can be obtained with relatively little effort on the part of the developer. Our experience is not limited to PRMs. In particular, we outline general techniques for parallelizing types of computations commonly performed in motion planning algorithms, and identify potential difficulties that might be faced in other efforts to parallelize sequential motion planning methods. 

@inproceedings{Amato-prmaep-1999, 
 author = {Amato, N.M. and Dale, L.K.}, 
 booktitle = {Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C)}, 
 doi = {10.1109/ROBOT.1999.770055}, 
 number = {}, 
 pages = {688-694 vol.1}, 
 title = {Probabilistic roadmap methods are embarrassingly parallel}, 
 volume = {1}, 
 year = {1999} 
}