Approaches for Heuristically Biasing RRT Growth
Conference Paper, Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol. 2, pp. 1178 - 1183, October, 2003
Abstract
This paper presents several modifications to the basic rapidly-exploring random tree (RRT) search algorithm. The fundamental idea is to utilize a heuristic quality function to guide the search. Results from a relevant simulation experiment illustrate the benefit and drawbacks of the developed algorithms. The paper concludes with several promising directions for future research.
BibTeX
@conference{Urmson-2003-8792,author = {Christopher Urmson and Reid Simmons},
title = {Approaches for Heuristically Biasing RRT Growth},
booktitle = {Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2003},
month = {October},
volume = {2},
pages = {1178 - 1183},
keywords = {Randomized Planning, RRT, path planning},
}
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