DocumentCode
292448
Title
Visual collision avoidance by segmentation
Author
Horswill, Ian
Author_Institution
Artificial Intelligence Lab., MIT, Cambridge, MA, USA
Volume
2
fYear
1994
fDate
12-16 Sep 1994
Firstpage
902
Abstract
Visual collision avoidance involves two difficult subproblems: obstacle recognition and depth measurement. We present a class of algorithms that use particularly simple methods for each subproblem and derive a set of sufficient conditions for their proper functioning based on a set of idealizations. We then discuss and compare two different implementations of the approach on mobile robots and discuss their performance. Finally, we experimentally validate the idealizations
Keywords
image segmentation; mobile robots; navigation; object recognition; path planning; robot vision; depth measurement; image segmentation; mobile robots; navigation; obstacle recognition; sufficient conditions; visual collision avoidance; Artificial intelligence; Cameras; Collision avoidance; Contracts; Laboratories; Petroleum; Pixel; Robots; Testing; Vehicle dynamics;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Robots and Systems '94. 'Advanced Robotic Systems and the Real World', IROS '94. Proceedings of the IEEE/RSJ/GI International Conference on
Conference_Location
Munich
Print_ISBN
0-7803-1933-8
Type
conf
DOI
10.1109/IROS.1994.407486
Filename
407486
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