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Slip prediction using visual information

Angelova, Anelia and Matthies, Larry and Helmick, Daniel and Perona, Pietro (2007) Slip prediction using visual information. In: Robotics : Science and Systems II. MIT Press , Cambridge, MA. ISBN 9780262693486. https://resolver.caltech.edu/CaltechAUTHORS:20150904-110638872

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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.


Item Type:Book Section
Related URLs:
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http://www.roboticsproceedings.org/rss02/p14.htmlOrganizationArticle
ORCID:
AuthorORCID
Perona, Pietro0000-0002-7583-5809
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.
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Funding AgencyGrant Number
NASA/JPL/CaltechUNSPECIFIED
Record Number:CaltechAUTHORS:20150904-110638872
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20150904-110638872
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:60075
Collection:CaltechAUTHORS
Deposited By: Caroline Murphy
Deposited On:15 Sep 2015 23:31
Last Modified:03 Oct 2019 08:53

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