Detecting obstacles and drop-offs using stereo and motion cues for safe local motion

A mobile robot operating in an urban environment has to navigate around obstacles and hazards. Though a significant amount of work has been done on detecting obstacles, not much attention has been given to the detection of drop-offs, e.g., sidewalk curbs, downward stairs, and other hazards where an...

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Bibliographic Details
Main Authors: Murarka, A., Sridharan, M., Kuipers, B.
Format: Conference Proceeding
Language:English
Subjects:
Image color analysis
Image edge detection
Image segmentation
Robot kinematics
Robots
Safety
Three dimensional displays
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Summary:A mobile robot operating in an urban environment has to navigate around obstacles and hazards. Though a significant amount of work has been done on detecting obstacles, not much attention has been given to the detection of drop-offs, e.g., sidewalk curbs, downward stairs, and other hazards where an error could lead to disastrous consequences. In this paper, we propose algorithms for detecting both obstacles and drop-offs (also called negative obstacles) in an urban setting using stereo vision and motion cues. We propose a global color segmentation stereo method and compare its performance at detecting hazards against prior work using a local correlation stereo method. Furthermore, we introduce a novel drop-off detection scheme based on visual motion cues that adds to the performance of the stereo-vision methods. All algorithms are implemented and evaluated on data obtained by driving a mobile robot in urban environments.
ISSN:2153-0858
2153-0866
DOI:10.1109/IROS.2008.4651106