• DOI:10.1109/ROBOT.2005.1570709
Corpus ID: 745300

Dynamic-Domain RRTs: Efficient Exploration by Controlling the Sampling Domain

@article{Yershova2005DynamicDomainRE,
  title={Dynamic-Domain RRTs: Efficient Exploration by Controlling the Sampling Domain},
  author={A. Yershova and L. Jaillet and T. Sim{\'e}on and S. LaValle},
  journal={Proceedings of the 2005 IEEE International Conference on Robotics and Automation},
  year={2005},
  pages={3856-3861}
}

A. Yershova, L. Jaillet, +1 author S. LaValle

Published 2005

Computer Science

Proceedings of the 2005 IEEE International Conference on Robotics and Automation

Sampling-based planners have solved difficult problems in many applications of motion planning in recent years. In particular, techniques based on the Rapidly-exploring Random Trees (RRTs) have generated highly successful single-query planners. Even though RRTs work well on many problems, they have weaknesses which cause them to explore slowly when the sampling domain is not well adapted to the problem. In this paper we characterize these issues and propose a general framework for minimizing… CONTINUE READING

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