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Proceedings Paper

Iterative learning control technique for mobile robot path-tracking control
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Paper Abstract

Iterative learning control (ILC) is a technique for using repetitive operation to derive the input commands needed to force a dynamical system to follow a prescribed trajectory. In this paper we describe ideas towards the use of ILC for path-tracking control of a mobile robot. The work is focused on a novel robotic platform, the Utah State University (USU) Omni-Directional Vehicle (ODV), which features six “smart wheels,” each of which has independent control of both speed and direction. Using a validated dynamic model of the ODV robot, it is shown that ILC can be used to learn the nominal input commands needed force the robot to track a prescribed path in inertial space.

Paper Details

Date Published: 15 November 1999
PDF: 12 pages
Proc. SPIE 3838, Mobile Robots XIV, (15 November 1999); doi: 10.1117/12.369258
Show Author Affiliations
Kevin L. Moore, Utah State Univ. (United States)
Vikas Bahl, Utah State Univ. (United States)

Published in SPIE Proceedings Vol. 3838:
Mobile Robots XIV
Douglas W. Gage; Howie M. Choset, Editor(s)

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