NDLI: A CNN-based chip for robot locomotion control

Content Provider	IEEE Xplore Digital Library
Author	Arena, P. Fortuna, L. Frasca, M. Patane, L.
Copyright Year	2004
Abstract	In this paper, the paradigm of emergent computation is applied to locomotion control in legged robots: the locomotion gait is the result of self-organization of a network of locally coupled nonlinear oscillators. This means to adopt the biological paradigm of central pattern generator (CPG), implemented by using cellular neural networks (CNNs). The whole control strategy is hybrid in the sense that the gait generation is accomplished by a fully analog CNN, while a simple logic unit modulates the behavior of the CNN-based CPG, so that the strategy is suitable to eventually include sensory feedback. The design of a VLSI chip implementing the CNN-based CPG and some experimental results on the chip are presented. The chip is designed using a switched-capacitor technique, fundamental to obtain in a simple and direct way some key features of the hybrid control discussed. The experimental results confirm the suitability of the approach.
Sponsorship	IEEE Circuits and Systems Society
Starting Page	1862
Ending Page	1871
Page Count	10
File Size	1726691
File Format	PDF
ISSN	15498328
Volume Number	52
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot control Cellular neural networks Biology computing Computer networks Legged locomotion Robot sensing systems Couplings Local oscillators Hybrid power systems Logic locomotion control Analog very large-scale integration (VLSI) chip cellular neural network (CNN) central pattern generator (CPG) emergent computation
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Hardware and Architecture

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