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

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...

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Vydáno v:Control engineering practice Ročník 100; s. 104460
Hlavní autoři: Buşoniu, Lucian, Varma, Vineeth S., Lohéac, Jérôme, Codrean, Alexandru, Ştefan, Octavian, Morărescu, Irinel-Constantin, Lasaulce, Samson
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.07.2020
Elsevier
Témata:
Automatic
Engineering Sciences
Learning control
Mobile robots
Wireless communication
Wireless communication
Learning control
Mobile robots
ISSN:0967-0661, 1873-6939
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Shrnutí: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.
ISSN:0967-0661
1873-6939
DOI:10.1016/j.conengprac.2020.104460