Distributed online learning of central pattern generators in modular robots

Authors:
David Johan Christensen;Alexander Spröwitz;Auke Jan Ijspeert
Affiliations:
The Maersk Mc-Kinney Moller Institute, University of Southern Denmark;Biorobotics Laboratory, Ecole Polytechnique Fédérale de Lausanne, Switzerland;Biorobotics Laboratory, Ecole Polytechnique Fédérale de Lausanne, Switzerland
Venue:
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Year:
2010

Citing 3
Cited 2

Learning to Move in Modular Robots using Central Pattern Generators and Online Optimization

International Journal of Robotics Research
2008 Special Issue: Central pattern generators for locomotion control in animals and robots: A review

Neural Networks
Roombots: mechanical design of self-reconfiguring modular robots for adaptive furniture

ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation

Modular and reconfigurable mobile robotics

Robotics and Autonomous Systems
A distributed and morphology-independent strategy for adaptive locomotion in self-reconfigurable modular robots

Robotics and Autonomous Systems

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Abstract

In this paper we study distributed online learning of locomotion gaits for modular robots. The learning is based on a stochastic approximation method, SPSA, which optimizes the parameters of coupled oscillators used to generate periodic actuation patterns. The strategy is implemented in a distributed fashion, based on a globally shared reward signal, but otherwise utilizing local communication only. In a physics-based simulation of modular Roombots robots we experiment with online learning of gaits and study the effects of: module failures, different robot morphologies, and rough terrains. The experiments demonstrate fast online learning, typically 5-30 min. for convergence to high performing gaits (≅ 30 cm/sec), despite high numbers of open parameters (45-54). We conclude that the proposed approach is efficient, effective and a promising candidate for online learning on many other robotic platforms.