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Experiments in Vision-Laser Fusion using the Bayesian Occupancy Filter

John-David Yoder 1 Mathias Perrollaz 2 Igor Paromtchik 2 Yong Mao 2 Christian Laugier 2 
2 E-MOTION - Geometry and Probability for Motion and Action
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : Occupancy Grids have been used to represent the environment for some time. More recently, the Bayesian Occupancy Filter (BOF), which provides both an estimate of likelihood of occupancy of each cell, AND a probabilistic estimate of the velocity of each cell in the grid, has been introduced and patented. This work presents the first experiments in the use of the BOF to fuse data obtained from stereo vision and multiple laser sensors, on an intelligent vehicle platform. The paper describes the experimental platform, the approach to sensor fusion, and shows results from data captured in real traffic situations.
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Submitted on : Thursday, December 23, 2010 - 7:00:07 AM
Last modification on : Friday, November 18, 2022 - 9:23:03 AM
Long-term archiving on: : Friday, December 2, 2016 - 12:36:49 PM


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John-David Yoder, Mathias Perrollaz, Igor Paromtchik, Yong Mao, Christian Laugier. Experiments in Vision-Laser Fusion using the Bayesian Occupancy Filter. International Symposium on Experimental Robotics, Dec 2010, Delhi, India. ⟨inria-00538678⟩



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