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Neural Netw. 2008 May;21(4):642-53. doi: 10.1016/j.neunet.2008.03.014. Epub 2008 May 14.

Central pattern generators for locomotion control in animals and robots: a review.

Author information

1
School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne, Station 14, Lausanne, Switzerland. Auke.Ijspeert@epfl.ch

Abstract

The problem of controlling locomotion is an area in which neuroscience and robotics can fruitfully interact. In this article, I will review research carried out on locomotor central pattern generators (CPGs), i.e. neural circuits capable of producing coordinated patterns of high-dimensional rhythmic output signals while receiving only simple, low-dimensional, input signals. The review will first cover neurobiological observations concerning locomotor CPGs and their numerical modelling, with a special focus on vertebrates. It will then cover how CPG models implemented as neural networks or systems of coupled oscillators can be used in robotics for controlling the locomotion of articulated robots. The review also presents how robots can be used as scientific tools to obtain a better understanding of the functioning of biological CPGs. Finally, various methods for designing CPGs to control specific modes of locomotion will be briefly reviewed. In this process, I will discuss different types of CPG models, the pros and cons of using CPGs with robots, and the pros and cons of using robots as scientific tools. Open research topics both in biology and in robotics will also be discussed.

PMID:
18555958
DOI:
10.1016/j.neunet.2008.03.014
[Indexed for MEDLINE]

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