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High-Speed Autonomous Navigation with Motion Prediction for Unknown Moving Obstacles

Dizan Alejandro Vasquez Govea 1 Frédéric Large 1 Thierry Fraichard 1 Christian Laugier 1
1 E-MOTION - Geometry and Probability for Motion and Action
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes
Abstract : Vehicle navigation in dynamic environments is an important challenge, especially when the motion of the objects populating the environment is unknown. Traditional motion planning approaches are too slow to be applied in realtime to this domain, hence, new techniques are needed. Recently, iterative planning has emerged as a promising approach. Nevertheless, existing iterative methods do not provide a way to estimate the future behaviour of moving obstacles and use the resulting estimates in trajectory computation. This paper presents an iterative planning approach that addresses these two issues. It consists of two complementary methods: 1) a motion prediction method which learns typical behaviours of objects in a given environment. 2) an iterative motion planning technique based on the concept of Velocity Obstacles.
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Submitted on : Wednesday, October 24, 2007 - 6:44:44 PM
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  • HAL Id : inria-00182062, version 1




Dizan Alejandro Vasquez Govea, Frédéric Large, Thierry Fraichard, Christian Laugier. High-Speed Autonomous Navigation with Motion Prediction for Unknown Moving Obstacles. Proc. of the IEEE-RSJ Int. Conf. on Intelligent Robots and Systems, Oct 2004, Sendai (JP), France. pp.82--87. ⟨inria-00182062⟩



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