-
Detection, Estimation and Avoidance of Mobile Objects Using Stereo-Vision and Model Predictive Control
AbstractWe propose a complete loop (detection, estimation, avoidance) for the safe navigation of an autonomous vehicle in presence of dynamical obstacles. For detecting moving objects from stereo images and estimating their positions, two algorithms are proposed. The first one is dense and has a high computational load but is designed to fully exploit GPU processing. The second one is lighter and can run on a standard embedded processor. After a step of filtering, the estimated mobile objects are exploited in a model predictive control scheme for collision avoidance while tracking a reference trajectory. Experimental results with the complete loop are reported for a micro-air vehicle and a mobile robot in realistic situations, with everything computed on board.
Related Material
[pdf] [supp][bibtex]@InProceedings{Roggeman_2017_ICCV,
author = {Roggeman, Helene and Marzat, Julien and Derome, Maxime and Sanfourche, Martial and Eudes, Alexandre and Le Besnerais, Guy},
title = {Detection, Estimation and Avoidance of Mobile Objects Using Stereo-Vision and Model Predictive Control},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2017}
}
These ICCV 2017 papers are the Open Access versions, provided by the Computer Vision Foundation.
Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.
Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.
This material is presented to ensure timely dissemination of scholarly and technical work.
Copyright and all rights therein are retained by authors or by other copyright holders.
All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright.