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arXiv · 2011.09193

Learning control for transmission and navigation with a mobile robot under unknown communication rates

L. Busoniu·V. S. Varma·J. Loheac·A. Codrean·O. Stefan·I. -C. Morarescu·S. Lasaulce
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Abstract

In tasks such as surveying or monitoring remote regions, an autonomous robot must move while transmitting data over a wireless network with unknown, position-dependent transmission rates. For such a robot, this paper considers the problem of transmitting a data buffer in minimum time, while possibly also navigating towards a goal position. Two approaches are proposed, each consisting of a machine-learning component that estimates the rate function from samples; and of an optimal-control component that moves the robot given the current rate function estimate. Simple obstacle avoidance is performed for the case without a goal position. In extensive simulations, these methods achieve competitive performance compared to known-rate and unknown-rate baselines. A real indoor experiment is provided in which a Parrot AR.Drone 2 successfully learns to transmit the buffer.

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L. Busoniu, V. S. Varma, J. Loheac, A. Codrean, O. Stefan, I. -C. Morarescu, S. Lasaulce. 2020-11-18. Learning control for transmission and navigation with a mobile robot under unknown communication rates. https://arxiv.org/abs/2011.09193

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