Abstract
We examine the practical problem of a mobile autonomous robot performing a long-duration survey task, during which it must recharge its batteries periodically. We present a scalable, online, heuristic method that allows the robot to recharge efficiently, thus maximizing its rate of work. The method is a direct application of the rate-maximizing foraging model, which seeks to explain the behaviour of animals solving related problems. Simulation results suggest that the method performs very well compared to optimal and naive heuristic approaches.
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Wawerla, J., Vaughan, R.T. (2007). Near-Optimal Mobile Robot Recharging with the Rate-Maximizing Forager. In: Almeida e Costa, F., Rocha, L.M., Costa, E., Harvey, I., Coutinho, A. (eds) Advances in Artificial Life. ECAL 2007. Lecture Notes in Computer Science(), vol 4648. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74913-4_78
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DOI: https://doi.org/10.1007/978-3-540-74913-4_78
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