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Stereo Vision Based Terrain Mapping for Off-Road Autonomous NavigationSuccessful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as no-go regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.
Document ID
20150008338
Acquisition Source
Jet Propulsion Laboratory
Document Type
Conference Paper
External Source(s)
Authors
Rankin, Arturo L.
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Huertas, Andres
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Matthies, Larry H.
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
May 18, 2015
Publication Date
April 13, 2009
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Meeting Information
Meeting: SPIE Defense, Security and Sensing Conference
Location: Orlando, FL
Country: United States
Start Date: April 13, 2009
End Date: April 17, 2009
Sponsors: International Society for Optical Engineering
Distribution Limits
Public
Copyright
Other
Keywords
passive perception

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