A NEW HYBRID SAMPLING STRATEGY FOR PRM PLANNERS - To Address Narrow Passages Problem
Sofiane Ahmed Ali, Eric Vasselin, Alain Faure
2006
Abstract
The probabilistic path planner (PPP) is a general planning scheme that yields fast robot path planners for a wide variety of problems, involving high degree of freedom articulated robots, non holonomic robots, and multiple robots. This paper presents a new probabilistic approach for finding paths through narrow passages. Our probabilistic planner follows the general framework of probabilistic roadmap (PRM), but to increase sample density in difficult areas like narrow passages, we define two sampling constraints in order to get much more points than a classic PRM gets in such areas. We simulate our planner in 2D environments and the simulations results shows good performance for our planner.
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in Harvard Style
Ali S., Vasselin E. and Faure A. (2006). A NEW HYBRID SAMPLING STRATEGY FOR PRM PLANNERS - To Address Narrow Passages Problem . In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-972-8865-60-3, pages 561-564. DOI: 10.5220/0001220405610564
in Bibtex Style
@conference{icinco06,
author={Sofiane Ahmed Ali and Eric Vasselin and Alain Faure},
title={A NEW HYBRID SAMPLING STRATEGY FOR PRM PLANNERS - To Address Narrow Passages Problem},
booktitle={Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2006},
pages={561-564},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001220405610564},
isbn={978-972-8865-60-3},
}
in EndNote Style
TY - CONF
JO - Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - A NEW HYBRID SAMPLING STRATEGY FOR PRM PLANNERS - To Address Narrow Passages Problem
SN - 978-972-8865-60-3
AU - Ali S.
AU - Vasselin E.
AU - Faure A.
PY - 2006
SP - 561
EP - 564
DO - 10.5220/0001220405610564