DocumentCode :
974156
Title :
Off-Road Path and Obstacle Detection Using Decision Networks and Stereo Vision
Author :
Caraffi, C. ; Cattani, S. ; Grisleri, P.
Author_Institution :
Univ. di Parma, Parma
Volume :
8
Issue :
4
fYear :
2007
Firstpage :
607
Lastpage :
618
Abstract :
Autonomous driving in off-road environments requires an exceptionally capable sensor system, particularly given that the unstructured environment does not provide many of the cues available in on-road environments. This paper presents a complex vision system, which is able to provide the two basic sensorial capabilities needed by autonomous vehicle navigation in extreme environments: obstacle detection and path detection. A variable-width-baseline (up to 1.5 m) single-frame stereo system is used for pitch estimation and obstacle detection, whereas a decision-network approach is used to detect the drivable path by a monocular vision system. The system has been field tested on the TerraMax vehicle, which is one of the only five vehicles to complete the 2005 Defense Advanced Research Projects Agency (DARPA) Grand Challenge course.
Keywords :
collision avoidance; mobile robots; road vehicles; robot vision; stereo image processing; TerraMax vehicle; autonomous driving; autonomous vehicle navigation; complex vision system; decision network; image stabilization; monocular vision system; obstacle detection; off-road path; path detection; pitch estimation; sensorial capability; stereo vision; variable-width-baseline; Application software; Artificial intelligence; Intelligent systems; Machine vision; Mobile robots; Navigation; Remotely operated vehicles; Sensor systems; Stereo vision; Vehicle detection; Autonomous vehicle; decision networks; image stabilization; obstacle detection; path detection; stereo;
fLanguage :
English
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1524-9050
Type :
jour
DOI :
10.1109/TITS.2007.908583
Filename :
4382936
Link To Document :
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