Learning to stop: a unifying principle for legged locomotion in varying environments

Thuruthel, T. G., Picardi, G., Iida, F. , Laschi, C. and Calisti, M. (2021) Learning to stop: a unifying principle for legged locomotion in varying environments. Royal Society Open Science, 8 (4). ISSN 2054-5703

Full content URL: https://doi.org/10.1098/rsos.210223

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Learning to stop: a unifying principle for legged locomotion in varying environments
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Abstract

Evolutionary studies have unequivocally proven the transition of living organisms from water to land. Consequently, it can be deduced that locomotion strategies must have evolved from one environment to the other. However, the mechanism by which this transition happened and its implications on bio-mechanical studies and robotics research have not been explored in detail. This paper presents a unifying control strategy for locomotion in varying environments based on the principle of ‘learning to stop’. Using a common reinforcement learning framework, deep deterministic policy gradient, we show that our proposed learning strategy facilitates a fast and safe methodology for transferring learned controllers from the facile water environment to the harsh land environment. Our results not only propose a plausible mechanism for safe and quick transition of locomotion strategies from a water to land environment but also provide a novel alternative for safer and faster training of robots.

Keywords:Modelling., Legged locomotion, reinforcement learning
Subjects:H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G760 Machine Learning
Divisions:College of Science > Lincoln Institute for Agri-Food Technology
ID Code:44628
Deposited On:05 May 2021 11:06

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