To explore or to exploit? Learning humans' behaviour to maximize interactions with them

Kulich, Miroslav and Krajnik, Tomas and Preucil, Libor and Duckett, Tom (2016) To explore or to exploit? Learning humans' behaviour to maximize interactions with them. In: International Workshop on Modelling and Simulation for Autonomous Systems, 16 - 18 June 2016, Rome.

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Item Type:Conference or Workshop contribution (Paper)
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Abstract

Assume a robot operating in a public space (e.g., a library, a museum) and serving visitors as a companion, a guide or an information stand. To do that, the robot has to interact with humans, which presumes that it actively searches for humans in order to interact with them. This paper addresses the problem how to plan robot's actions in order to maximize the number of such interactions in the case human behavior is not known in advance. We formulate this problem as the exploration/exploitation problem and design several strategies for the robot. The main contribution of the paper than lies in evaluation and comparison of the designed strategies on two datasets. The evaluation shows interesting properties of the strategies, which are discussed.

Keywords:mobile robotics;, Human-robot interaction, spatio-temporal mapping
Subjects:H Engineering > H670 Robotics and Cybernetics
Divisions:College of Science > School of Computer Science
ID Code:26195
Deposited On:15 Feb 2017 10:08

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