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Fusion of stereo and optical flow data using occupancy grids

Christophe Braillon 1 Kane Usher 1 Cédric Pradalier 1 Jim Crowley 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 : In this paper, we propose a real-time method to detect obstacles using theoretical models of the ground plane, first in a 3D point cloud given by a stereo camera, and then in an optical flow field given by one of the stereo pair's camera. The idea of our method is to combine two partial occupancy grids from both sensor modalities with an occupancy grid framework. The two methods do not have the same range, precision and resolution. For example, the stereo method is precise for close objects but cannot see further than 7 m (with our lenses), while the optical flow method can see considerably further but has lower accuracy. Experiments that have been carried on the CyCab mobile robot and on a tractor demonstrate that we can combine the advantages of both algorithms to build local occupancy grids from incomplete data (optical flow from a monocular camera cannot give depth information without time integration).
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Submitted on : Wednesday, October 24, 2007 - 6:25:43 PM
Last modification on : Wednesday, February 2, 2022 - 3:58:18 PM
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  • HAL Id : inria-00182013, version 1



Christophe Braillon, Kane Usher, Cédric Pradalier, Jim Crowley, Christian Laugier. Fusion of stereo and optical flow data using occupancy grids. Proc. of the IEEE Int. Conf. on Intelligent Transportation Systems, Sep 2006, Toronto (CA), France. ⟨inria-00182013⟩



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