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Path planning with uncertainty: A set membership approach
Author(s) -
Ceccarelli Nicola,
Di Marco Mauro,
Garulli Andrea,
Giannitrapani Antonio,
Vicino Antonio
Publication year - 2011
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.1217
Subject(s) - motion planning , obstacle avoidance , mobile robot , path (computing) , range (aeronautics) , bounded function , set (abstract data type) , mathematical optimization , computer science , obstacle , robot , noise (video) , artificial intelligence , mathematics , engineering , geography , mathematical analysis , archaeology , image (mathematics) , programming language , aerospace engineering
The paper addresses the path planning problem in a set theoretic framework. The considered scenario is that of a mobile robot exploiting range and bearing measurements with respect to known landmarks to localize itself. By assuming unknown‐but‐bounded measurement noise, set membership localization techniques are used to estimate the uncertainty of each robot pose within the considered environment. The path planning problem is formulated and solved, with the aim of minimizing the total uncertainty associated with the travelled path. Practical issues such as limited sensory range and obstacle avoidance are taken into account. The proposed technique is validated via numerical simulations. Copyright © 2010 John Wiley & Sons, Ltd.