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Carnegie Mellon Robotics Institute

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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.

Keywords

Randomized Planning, RRT, path planning

Notes

Text Reference

Christopher Urmson and Reid Simmons, "Approaches for Heuristically Biasing RRT Growth," IEEE/RSJ IROS 2003, October, 2003.

BibTeX Reference

@inproceedings{Urmson_2003_4695,
   author = "Christopher Urmson and Reid Simmons",
   title = "Approaches for Heuristically Biasing RRT Growth",
   booktitle = "IEEE/RSJ IROS 2003",
   month = "October",
   year = "2003",
}

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