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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Neurorobot. | doi: 10.3389/fnbot.2019.00070

A Biomimetic Control Method Increases the Adaptability of a Humanoid Robot Acting in a Dynamic Environment

  • 1Technical University of Denmark, Denmark
  • 2Fortiss GmbH, Germany
  • 3Sant'Anna School of Advanced Studies, Italy

One of the big challenges in robotics is to endow agents with autonomous and adaptive capabilities. With this purpose, we embedded a cerebellum-based control system into a humanoid robot that becomes capable of handling dynamical external and internal complexity. The cerebellum is the area of the brain that coordinates and predicts the body movements throughout the body-environment interactions. Different biologically plausible cerebellar models are available in literature and have been employed for motor learning and control of simplified objects.
We built the canonical cerebellar microcircuit by combining machine learning and computational neuroscience techniques. The control system is composed of the adaptive cerebellar module and a classic control method; their combination allows a fast adaptive learning and robust control of the robotic movements when external disturbances appear. The control structure is built offline, but the dynamic parameters are learned during an online-phase training.
The aforementioned adaptive control system has been tested in the Neuro-robotics Platform with the virtual humanoid robot iCub. In the experiment, the robot iCub has to balance with the hand a table with a ball running on it. In contrast with previous attempts of solving this task, our results show that the robot takes advantage of its own past actions to perform the task. Furthermore, they confirm that the proposed neural controller is able to quickly adapt when the internal and external conditions change. Our bio-inspired and flexible control architecture can be applied to different robotic configurations without an excessive tuning of the parameters or customization. The cerebellum-based control system is indeed able to deal with changing dynamics and interactions with the environment. Important insights regarding the relationship between the bio-inspired control system functioning and the complexity of the task to be performed are obtained.

Keywords: Biomimetic, cerebellar control, motor learning, humanoid robot, Adaptive system, forward model, bio-inspired, neurorobotics

Received: 29 Jan 2019; Accepted: 12 Aug 2019.

Copyright: © 2019 Capolei, Angelidis, Falotico, Hautop Lund and Tolu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Mrs. Marie Claire Capolei, Technical University of Denmark, Kongens Lyngby, Denmark,
Dr. Silvia Tolu, Technical University of Denmark, Kongens Lyngby, Denmark,