A stereo vision based mapping algorithm for detecting inclines, drop-offs, and obstacles for safe local navigation

Mobile robots have to detect and handle a variety of potential hazards to navigate autonomously. We present a real-time stereo vision based mapping algorithm for identifying and modeling various hazards in urban environments - we focus on inclines, drop-offs, and obstacles. In our algorithm, stereo...

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Bibliographic Details
Published in2009 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 1646 - 1653
Main Authors Murarka, A., Kuipers, B.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2009
Subjects
Clouds
Computer science
Hazards
Mobile robots
Navigation
Path planning
Robot kinematics
Rough surfaces
Safety
Stereo vision
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ISBN9781424438037
1424438039
ISSN2153-0858
DOI10.1109/IROS.2009.5354253

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Summary:Mobile robots have to detect and handle a variety of potential hazards to navigate autonomously. We present a real-time stereo vision based mapping algorithm for identifying and modeling various hazards in urban environments - we focus on inclines, drop-offs, and obstacles. In our algorithm, stereo range data is used to construct a 3D model consisting of a point cloud with a 3D grid overlaid on top. A novel plane fitting algorithm is then used to segment the 3D model into distinct potentially traversable ground regions and fit planes to the regions. The planes and segments are analyzed to identify safe and unsafe regions and the information is captured in an annotated 2D grid map called a local safety map. The safety map can be used by wheeled mobile robots for planning safe paths in their local surroundings. We evaluate our algorithm comprehensively by testing it in varied environments and comparing the results to ground truth data.
ISBN:9781424438037
1424438039
ISSN:2153-0858
DOI:10.1109/IROS.2009.5354253