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conference paper · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · 2003

The Gaussian sampling strategy for probabilistic roadmap planners

V. Boor, Mark H. Overmars, A. Frank van der Stappen

Cited by 548Abstract and details only

Abstract

Probabilistic roadmap planners (PRMs) form a relatively new technique for motion planning that has shown great potential. A critical aspect of PRM is the probabilistic strategy used to sample the free configuration space. In this paper we present a new, simple sampling strategy, which we call the Gaussian sampler, that gives a much better coverage of the difficult parts of the free configuration space. The approach uses only elementary operations which makes it suitable for many different planning problems. Experiments indicate that the technique is very efficient indeed.

Cite this paper

APA 7

Boor, V., Overmars, M. H., & van der Stappen, A. F. (2003). The Gaussian sampling strategy for probabilistic roadmap planners. Proceedings - IEEE International Conference on Robotics and Automation/Proceedings, 2, 1018–1023. https://doi.org/10.1109/robot.1999.772447

MLA 9

Boor, V., et al. “The Gaussian sampling strategy for probabilistic roadmap planners.” Proceedings - IEEE International Conference on Robotics and Automation/Proceedings, vol. 2, 2003, pp. 1018–23, https://doi.org/10.1109/robot.1999.772447.

Chicago

Boor, V., Mark H. Overmars, and A. Frank van der Stappen. 2003. “The Gaussian sampling strategy for probabilistic roadmap planners.” Proceedings - IEEE International Conference on Robotics and Automation/Proceedings 2: 1018–23. https://doi.org/10.1109/robot.1999.772447.

Harvard

Boor, V., Overmars, M.H. and van der Stappen, A.F. (2003) ‘The Gaussian sampling strategy for probabilistic roadmap planners’, Proceedings - IEEE International Conference on Robotics and Automation/Proceedings, 2, pp. 1018–1023. Available at: https://doi.org/10.1109/robot.1999.772447.

BibTeX
@article{boor2003gaussian,
  title = {{The Gaussian sampling strategy for probabilistic roadmap planners}},
  author = {Boor, V. and Overmars, Mark H. and van der Stappen, A. Frank},
  journal = {Proceedings - IEEE International Conference on Robotics and Automation/Proceedings},
  volume = {2},
  pages = {1018--1023},
  year = {2003},
  doi = {10.1109/robot.1999.772447}
}

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