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Efficient environment representation for mobile robot path planning using CVT-PRM with Halton sampling

Efficient environment representation for mobile robot path planning using CVT-PRM with Halton sampling

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A centroidal Voronoi tessellation-based probabilistic roadmap (CVT-PRM) and its construction method for mobile robot path planning are introduced. The CVT-PRM efficiently encoded the entire unoccupied region of the environment by autonomously rearranging the positions of nodes via CVT and Halton sampling. Simulation results verified that the CVT-PRM can encode the entire unoccupied region efficiently, using evenly distributed nodes.

References

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      • van den Berg, J., Ferguson, D., Kuffner, J.: `Anytime path planning and replanning in dynamic environments', Proc. IEEE Int. Conf. on Robotics and Automation, May 2006, Orlando, FL, USA, p. 2366–2371.
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http://iet.metastore.ingenta.com/content/journals/10.1049/el.2012.2894
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