Abstract
As mobile robots become increasingly autonomous over extended periods of time, opportunities arise for their use on repetitive tasks. We define and implement behaviors for a class of such tasks that we call continuous area sweeping tasks. A continuous area sweeping task is one in which a group of robots must repeatedly visit all points in a fixed area, possibly with non-uniform frequency, as specified by a task-dependent cost function. Examples of problems that need continuous area sweeping are trash removal in a large building and routine surveillance. We present a formulation for this problem and an initial algorithm to address it. The approach is analyzed analytically and is fully implemented and tested, both in simulation and on physical robots.
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Ahmadi, M., Stone, P. (2006). Multi-robot Learning for Continuous Area Sweeping. In: Tuyls, K., Hoen, P.J., Verbeeck, K., Sen, S. (eds) Learning and Adaption in Multi-Agent Systems. LAMAS 2005. Lecture Notes in Computer Science(), vol 3898. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11691839_2
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DOI: https://doi.org/10.1007/11691839_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33053-0
Online ISBN: 978-3-540-33059-2
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