Abstract
To learn a map of an environment a mobile robot has to explore its workspace. This paper introduces a new exploration approach that minimizes movements of the robot to reach the nearest unexplored region of the environment. In contrast to other methods, this approach takes into account rotations of the robot as well as the distance traveled by the robot, to compute an optimal movement policy to reach the nearest unexplored region. The robot acquires a kind of inertial mass that decreases the number of movements that changes the orientation of the robot, and hence reduces odometric errors. This approach is tested using a mobile robot simulator with very good results.
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Romero, L., Morales, E.F., Sucar, L.E. (2002). An Exploration Approach for Indoor Mobile Robots Reducing Odometric Errors. In: Coello Coello, C.A., de Albornoz, A., Sucar, L.E., Battistutti, O.C. (eds) MICAI 2002: Advances in Artificial Intelligence. MICAI 2002. Lecture Notes in Computer Science(), vol 2313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46016-0_6
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DOI: https://doi.org/10.1007/3-540-46016-0_6
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