Learning control for transmission and navigation with a mobile robot under unknown communication rates. (July 2020)

• Record Type: Journal Article
• Authors: Buşoniu, Lucian; Varma, Vineeth S.; Lohéac, Jérôme; Codrean, Alexandru; Ştefan, Octavian; Morărescu, Irinel-Constantin; Lasaulce, Samson
• Is Part Of: Control engineering practice. Volume 100(2020)
• Publication Date: 2020-07
• Subjects: Learning control -- Wireless communication -- Mobile robots; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2020.104460
• Languages: English
• ISSNs: 0967-0661

Abstract

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.