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Robust autonomous robot tracking using interval analysis

Abstract : This paper deals with robust and autonomous robot tracking using distance measurements provided by a belt of on-board ultrasonic sensors. The measurements errors are assumed to be bounded. The method presented uses a sey-valued nonlinear state estimator. As a Kalman filter, it alternates prediction based on past data and correction to take new measurements into account. Special attention is paid to the treatment of outliers due, e.g., to a partially outdated map or to faulty sensors.
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Contributor : Marie-Françoise Gerard <>
Submitted on : Tuesday, July 16, 2013 - 11:50:43 AM
Last modification on : Saturday, April 25, 2020 - 4:16:09 PM
Document(s) archivé(s) le : Thursday, October 17, 2013 - 4:16:10 AM


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  • HAL Id : hal-00844976, version 1


Michel Kieffer, Luc Jaulin, Eric Walter, Dominique Meizel. Robust autonomous robot tracking using interval analysis. IFAC-SYSID 2000, System Identification Congress 2000, Jun 2000, Santa-Barbara (California), United States. pp.x-x. ⟨hal-00844976⟩



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