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Conference Papers Year : 2008

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

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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.
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Dates and versions

inria-00332595 , version 1 (21-10-2008)

Identifiers

  • HAL Id : inria-00332595 , version 1

Cite

Chiara Fulgenzi, Christopher Tay, Anne Spalanzani, Christian Laugier. Probabilistic navigation in dynamic environment using Rapidly-exploring Random Trees and Gaussian Processes. IEEE/RSJ 2008 International Conference on Intelligent RObots and Systems, Sep 2008, Nice, France. ⟨inria-00332595⟩
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