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Effect of compliance on morphological control of dynamic locomotion with HyQ

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Abstract

Classic control theory applied to compliant and soft robots generally involves an increment of computation that has no equivalent in biology. To tackle this, morphological computation describes a theoretical framework that takes advantage of the computational capabilities of physical bodies. However, concrete applications in robotic locomotion control are still rare. Also, the trade-off between compliance and the capacity of a physical body to facilitate its own control has not been thoroughly studied in a real locomotion task. In this paper, we address these two problems on the state-of-the-art hydraulic robot HyQ. An end-to-end neural network is trained to control HyQ’s joints positions and velocities using only Ground Reaction Forces. Our simulations and experiments demonstrate better controllability using less memory and computational resources when increasing compliance. However, we show empirically that this effect cannot be attributed to the ability of the body to perform intrinsic computation. It invites to give an increased emphasis on compliance and co-design of the controller and the robot to facilitate attempts in machine learning locomotion.

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Acknowledgements

This research was supported by the HBP Neurorobotics Platform funded from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2). Experiments were conducted on the HyQ Platform hosted and funded by the Fondazione Istituto Italiano di Tecnologia. The authors would also like to thank Shamel Fahmi for his help during the experiments and Gennaro Raiola for his support with the software.

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Authors and Affiliations

  1. IDLab-AIRO, elis, Ghent University – imec, Ghent, Belgium

    Gabriel Urbain, Joni Dambre & Francis wyffels

  2. Dynamic Legged Systems (DLS) Lab, Istituto Italiano di Tecnologia (IIT), Genova, Italy

    Victor Barasuol & Claudio Semini

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  1. Gabriel Urbain
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  2. Victor Barasuol
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  3. Claudio Semini
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  4. Joni Dambre
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  5. Francis wyffels
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GU, VB, and Fw conceived the study, designed the experiments, and interpreted the results. GU and VB conducted the experiments. GU wrote the manuscript and all authors reviewed it.

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Correspondence to Gabriel Urbain.

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Urbain, G., Barasuol, V., Semini, C. et al. Effect of compliance on morphological control of dynamic locomotion with HyQ. Auton Robot 45, 421–434 (2021). https://doi.org/10.1007/s10514-021-09974-9

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