Skip to Main content Skip to Navigation
Conference papers

Moving Obstacles' Motion Prediction for Autonomous Navigation

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 real-time 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 es- timate the future behavior of moving obstacles and use the resulting estimates in trajectory computa- tion. This paper presents an iterative planning ap- proach that addresses these two issues. It consists of two complementary methods: 1) a motion prediction method which learns typical behaviors of objects in a given environment. 2) an iterative motion planning technique based on the concept of Velocity Obsta- cles.
Document type :
Conference papers
Complete list of metadata
Contributor : Christian Laugier Connect in order to contact the contributor
Submitted on : Wednesday, October 24, 2007 - 6:46:21 PM
Last modification on : Monday, December 28, 2020 - 3:44:02 PM
Long-term archiving on: : Monday, April 12, 2010 - 12:35:07 AM


Files produced by the author(s)


  • HAL Id : inria-00182067, version 1




Dizan Alejandro Vasquez Govea, Frédéric Large, Thierry Fraichard, Christian Laugier. Moving Obstacles' Motion Prediction for Autonomous Navigation. Proc. of the Int. Conf. on Control, Automation, Robotics and Vision, Dec 2004, Kunming, China, France. ⟨inria-00182067⟩



Les métriques sont temporairement indisponibles