This paper addresses the simultaneous localization and mapping problem in an environment where indistinguishable landmarks can be detected. A set theoretic approach to the problem is presented. Algorithms for measurement-to-feature matching, estimation of landmark positions, estimation of robot location and heading are derived in terms of uncertainty regions, under the hypothesis that errors affecting all sensor measurements are unknown-but-bounded. The proposed technique is validated in an experimental setup. Copyright © 2002 IFAC.
Di Marco, M., Garulli, A., Giannitrapani, A., Vicino, A. (2002). Dynamic robot localization and mapping using uncertainty sets. In Proceedings of the 15th IFAC World Congress (pp.281-286). IFAC Secretariat [10.3182/20020721-6-ES-1901.00859].
Dynamic robot localization and mapping using uncertainty sets
Di Marco, M.;Garulli, A.;Giannitrapani, A.;Vicino, A.
2002-01-01
Abstract
This paper addresses the simultaneous localization and mapping problem in an environment where indistinguishable landmarks can be detected. A set theoretic approach to the problem is presented. Algorithms for measurement-to-feature matching, estimation of landmark positions, estimation of robot location and heading are derived in terms of uncertainty regions, under the hypothesis that errors affecting all sensor measurements are unknown-but-bounded. The proposed technique is validated in an experimental setup. Copyright © 2002 IFAC.
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https://hdl.handle.net/11365/2947
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