AI in locomotion: challenges and perspectives of underactuated robots

Authors:
Fumiya Iida;Rolf Pfeifer;André Seyfarth
Affiliations:
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA and Artificial Intelligence Laboratory, Department of Informatics, University of Zuric ...;Artificial Intelligence Laboratory, Department of Informatics, University of Zurich, Zurich, Switzerland;Locomotion Laboratory, University of Jena, Jena, Germany
Venue:
50 years of artificial intelligence
Year:
2007

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Abstract

This article discusses the issues of adaptive autonomous navigation as a challenge of artificial intelligence. We argue that, in order to enhance the dexterity and adaptivity in robot navigation, we need to take into account the decentralized mechanisms which exploit physical system-environment interactions. In this paper, by introducing a few underactuated locomotion systems, we explain (1) how mechanical body structures are related to motor control in locomotion behavior, (2) how a simple computational control process can generate complex locomotion behavior, and (3) how a motor control architecture can exploit the body dynamics through a learning process. Based on the case studies, we discuss the challenges and perspectives toward a new framework of adaptive robot control.