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Probabilistic navigation in dynamic environment using Rapidly-exploring Random Trees and Gaussian Processes
Abstract : The paper describes a navigation algorithm for dynamic, uncertain environment. Moving obstacles are supposed to move on typical patterns which are pre-learned and are represented by Gaussian processes. The planning algorithm is based on an extension of the Rapidly-exploring Random Tree algorithm, where the likelihood of the obstacles 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 of the navigation algorithm for a car-like robot moving among dynamic obstacles with probabilistic trajectory prediction.
https://hal.inria.fr/inria-00332595
Contributor : Chiara Fulgenzi Connect in order to contact the contributor
Submitted on : Tuesday, October 21, 2008 - 11:32:41 AM
Last modification on : Thursday, January 20, 2022 - 5:27:13 PM
Long-term archiving on: : Monday, June 7, 2010 - 7:06:14 PM
Contributor : Chiara Fulgenzi Connect in order to contact the contributor
Submitted on : Tuesday, October 21, 2008 - 11:32:41 AM
Last modification on : Thursday, January 20, 2022 - 5:27:13 PM
Long-term archiving on: : Monday, June 7, 2010 - 7:06:14 PM
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