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Risk based motion planning and navigation in uncertain dynamic environment

Chiara Fulgenzi 1 Anne Spalanzani 1 Christian Laugier 1 Christopher Tay 1 
1 E-MOTION - Geometry and Probability for Motion and Action
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : Navigation in large dynamic spaces has been often adressed using deterministic representations, fast updating and reactive avoidance strategies. However, probabilistic representations are much more informative and their use in mapping and prediction methods improves the quality of obtained results. The paper proposes a new concept to integrate a probabilist collision risk function linking planning and navigation methods with the perception and the prediction of the dynamic environments. Moving obstacles are supposed to move along typical motion patterns represented by Gaussian Processes. The likelihood of the obstacles' future trajectory and the probability of occupation are used to compute the risk of collision. The proposed planning algorithm is a sampling-based partial planner guided by the risk of collision. The perception and prediction information are updated on-line and reused by the planner. The decision takes into account the most recent estimation. Results show the performance for a robotic wheelchair in a simulated environment among multiple dynamic obstacles.
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Submitted on : Tuesday, October 19, 2010 - 1:38:07 PM
Last modification on : Wednesday, October 26, 2022 - 8:16:19 AM
Long-term archiving on: : Thursday, January 20, 2011 - 2:28:09 AM


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  • HAL Id : inria-00526601, version 1


Chiara Fulgenzi, Anne Spalanzani, Christian Laugier, Christopher Tay. Risk based motion planning and navigation in uncertain dynamic environment. [Research Report] 2010, pp.14. ⟨inria-00526601⟩



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