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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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Submitted on : Wednesday, June 24, 2009 - 11:06:44 AM
Last modification on : Saturday, June 25, 2022 - 7:36:07 PM
Long-term archiving on: : Tuesday, June 15, 2010 - 6:33:47 PM


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  • HAL Id : inria-00398059, version 1



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. ⟨inria-00398059⟩



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