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Avoiding Cars and Pedestrians using V-Obstacles and Motion Prediction

Frédéric Large 1 Dizan Alejandro Vasquez Govea 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 real-time to this domain, hence, new techniques are needed. Recently, iterative planning has emerged as a promising approach. Nevertheless, existing iterative methods don't provide a way to estimating the future behaviour of moving obstacles and to 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 - 6:43:22 PM
Last modification on : Thursday, January 20, 2022 - 4:12:44 PM
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  • HAL Id : inria-00182054, version 1



Frédéric Large, Dizan Alejandro Vasquez Govea, Thierry Fraichard, Christian Laugier. Avoiding Cars and Pedestrians using V-Obstacles and Motion Prediction. Proc. of the IEEE Intelligent Vehicle Symp., Jun 2004, Pisa (IT), France. ⟨inria-00182054⟩



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