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2008
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Probabilistic navigation in dynamic environment using Rapidly-exploring Random Trees and Gaussian processes

10 years 4 months ago
Probabilistic navigation in dynamic environment using Rapidly-exploring Random Trees and Gaussian processes
— 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.
Chiara Fulgenzi, Christopher Tay, Anne Spalanzani,
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where IROS
Authors Chiara Fulgenzi, Christopher Tay, Anne Spalanzani, Christian Laugier
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