Occupancy grids from stereo and optical flow data

Christophe Braillon 1 Cédric Pradalier 1 Kane Usher 1 Jim Crowley 1 Christian Laugier 1
1 E-MOTION - Geometry and Probability for Motion and Action
GRAVIR - IMAG - Graphisme, Vision et Robotique, 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).
Document type :
Conference papers
Complete list of metadatas

Cited literature [16 references]  Display  Hide  Download

https://hal.inria.fr/inria-00182020
Contributor : Christian Laugier <>
Submitted on : Wednesday, October 24, 2007 - 6:26:36 PM
Last modification on : Thursday, January 3, 2019 - 11:06:03 AM
Long-term archiving on : Monday, September 24, 2012 - 2:35:41 PM

File

BPUCL06.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00182020, version 1

Collections

INRIA | UGA | IMAG

Citation

Christophe Braillon, Cédric Pradalier, Kane Usher, Jim Crowley, Christian Laugier. Occupancy grids from stereo and optical flow data. Proc. of the Int. Symp. on Experimental Robotics, Jul 2006, Rio de Janeiro (BR), France. ⟨inria-00182020⟩

Share

Metrics

Record views

300

Files downloads

575