Probabilistic motion planning among moving obstacles following typical motion patterns.

Chiara Fulgenzi 1 Anne Spalanzani 1 Christian Laugier 1
1 E-MOTION - Geometry and Probability for Motion and Action
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : The paper presents a navigation algorithm for dynamic, uncertain environment. The static environment is unknown, while moving pedestrians are detected and tracked on-line. Pedestrians are supposed to move along typical motion patterns represented by HMMs. The planning algorithm is based on an extension of the Rapidly-exploring Random Tree algorithm, where the likelihood of the obstacles future trajectory and the probability of collision is explicitly taken into account. The algorithm is used in a partial motion planner, and the probability of collision is updated in real-time according to the most recent estimation. Results show the performance for a car-like robot in a simulated environment among multiple dynamic obstacles.
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Communication dans un congrès
IEEE/RSJ International Conference on Intelligent RObots and Systems, Oct 2009, St. Louis, Missouri, United States. 2009
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Dernière modification le : mercredi 11 avril 2018 - 01:54:10
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Chiara Fulgenzi, Anne Spalanzani, Christian Laugier. Probabilistic motion planning among moving obstacles following typical motion patterns.. IEEE/RSJ International Conference on Intelligent RObots and Systems, Oct 2009, St. Louis, Missouri, United States. 2009. 〈inria-00398059〉

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