Slip prediction using visual information
Abstract
This paper considers prediction of slip from a distance for wheeled ground robots using visual information as input. Large amounts of slippage which can occur on certain surfaces, such as sandy slopes, will negatively affect rover mobility. Therefore, obtaining information about slip before entering a particular terrain can be very useful for better planning and avoiding terrains with large slip. The proposed method is based on learning from experience and consists of terrain type recognition and nonlinear regression modeling. After learning, slip prediction is done remotely using only the visual information as input. The method has been implemented and tested offline on several off-road terrains including: soil, sand, gravel, and woodchips. The slip prediction error is about 20% of the step size.
Additional Information
© 2007 MIT Press. This research was carried out by the JPL, California Institute of Technology, under a contract with NASA, with funding from the Mars Technology Program. Thanks also to the JPL LAGR team for giving us access to the vehicle and to the reviewers of the paper for many useful comments.Attached Files
Published - AngelovaRSS06_SlipPrediction.pdf
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Additional details
- Eprint ID
- 60075
- Resolver ID
- CaltechAUTHORS:20150904-110638872
- NASA/JPL/Caltech
- Created
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2015-09-15Created from EPrint's datestamp field
- Updated
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2019-10-03Created from EPrint's last_modified field