Toward Lifelong Affordance Learning Using a Distributed Markov Model

Robots are able to learn how to interact with objects by developing computational models of affordance. This paper presents an approach in which learning and operation occur concurrently, toward achieving lifelong affordance learning. In a such a regime a robot must be able to learn about new object...

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Veröffentlicht in:	IEEE transactions on cognitive and developmental systems 2018-03, Vol.10 (1), p.44-55
Hauptverfasser:	Glover, Arren J., Wyeth, Gordon F.
Format:	Artikel
Sprache:	eng
Schlagworte:	Affordance Computational modeling Floors Infrared detectors Learning Markov analysis Markov chains Markov model Markov processes mobile robot Mobile robots Robot kinematics Robot sensing systems Robots Visualization
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