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Proceedings Paper

Bayes filter modification for drivability map estimation with observations from stereo vision
Author(s): Aleksei Panchenko; Viktor Prun; Dmitri Turchenkov
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Paper Abstract

Reconstruction of a drivability map for a moving vehicle is a well-known research topic in applied robotics. Here creating such a map for an autonomous truck on a generally planar surface containing separate obstacles is considered. The source of measurements for the truck is a calibrated pair of cameras. The stereo system detects and reconstructs several types of objects, such as road borders, other vehicles, pedestrians and general tall objects or highly saturated objects (e.g. road cone). For creating a robust mapping module we use a modification of Bayes filtering, which introduces some novel techniques for occupancy map update step. Specifically, our modified version becomes applicable to the presence of false positive measurement errors, stereo shading and obstacle occlusion. We implemented the technique and achieved real-time 15 FPS computations on an industrial shake proof PC. Our real world experiments show the positive effect of the filtering step.

Paper Details

Date Published: 8 February 2017
PDF: 5 pages
Proc. SPIE 10253, 2016 International Conference on Robotics and Machine Vision, 102530C (8 February 2017); doi: 10.1117/12.2266461
Show Author Affiliations
Aleksei Panchenko, JSC «Cognitive» (Russian Federation)
Viktor Prun, JSC «Cognitive» (Russian Federation)
Dmitri Turchenkov, JSC «Cognitive» (Russian Federation)

Published in SPIE Proceedings Vol. 10253:
2016 International Conference on Robotics and Machine Vision
Alexander V. Bernstein; Adrian Olaru; Jianhong Zhou, Editor(s)

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