A multi-element generalized polynomial chaos approach to analysis of mobile robot dynamics under uncertainty

The ability of mobile robots to quickly and accurately analyze their dynamics is critical to their safety and efficient operation. In field conditions, significant uncertainty is associated with terrain and/or vehicle parameter estimates, and this must be considered in an analysis of robot motion. H...

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Bibliographic Details
Main Authors: Kewlani, Gaurav (Contributor), Iagnemma, Karl (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor), Massachusetts Institute of Technology. Laboratory for Manufacturing and Productivity (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers, 2010-10-21T15:31:41Z.
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Online Access:Get fulltext
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042 |a dc 
100 1 0 |a Kewlani, Gaurav  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Mechanical Engineering  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Laboratory for Manufacturing and Productivity  |e contributor 
100 1 0 |a Iagnemma, Karl  |e contributor 
100 1 0 |a Kewlani, Gaurav  |e contributor 
100 1 0 |a Iagnemma, Karl  |e contributor 
700 1 0 |a Iagnemma, Karl  |e author 
245 0 0 |a A multi-element generalized polynomial chaos approach to analysis of mobile robot dynamics under uncertainty 
260 |b Institute of Electrical and Electronics Engineers,   |c 2010-10-21T15:31:41Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/59443 
520 |a The ability of mobile robots to quickly and accurately analyze their dynamics is critical to their safety and efficient operation. In field conditions, significant uncertainty is associated with terrain and/or vehicle parameter estimates, and this must be considered in an analysis of robot motion. Here a Multi-Element generalized Polynomial Chaos (MEgPC) approach is presented that explicitly considers vehicle parameter uncertainty for long term estimation of robot dynamics. It is shown to be an improvement over the generalized Askey polynomial chaos framework as well as the standard Monte Carlo scheme, and can be used for efficient, accurate prediction of robot dynamics. 
520 |a United States. Army Research Office (contract number W912HZ-08-C-0062) 
546 |a en_US 
655 7 |a Article 
773 |t IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009. IROS 2009