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

@article{Yershova2005DynamicDomainRE,
  title={Dynamic-Domain RRTs: Efficient Exploration by Controlling the Sampling Domain},
  author={Anna Yershova and L{\'e}onard Jaillet and Thierry Sim{\'e}on and Steven M. LaValle},
  journal={Proceedings of the 2005 IEEE International Conference on Robotics and Automation},
  year={2005},
  pages={3856-3861}
}
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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