An integrated motor control loop of a human-like robotic arm: Feedforward, feedback and cerebellum-based learning

C. Casellato, A. Pedrocchi, J. A. Garrido, N. R. Luque, G. Ferrigno, E. D'Angelo, E. Ros

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A new complex model of human motor control has been developed, combining brain internal models and neural network mechanisms. Based on nervous system structures and operating principles, a feedforward block, a feedback controller and a cerebellum-like learning module have been integrated and tested with an anthropometric robotic arm. A simulated sequence of 8-like tracking tasks showed the contributions of these main loops over time. Different external dynamics were introduced. The role of feedback corrections, intrinsically imprecise due to sensorimotor delays, decreases, while the output of cerebellum, which has been learning, increases; the movement becomes more accurate. Moreover, an experimental session on a subject performing the task repetitions using a haptic device was carried out, recording upper limb kinematics.

Original languageEnglish
Title of host publicationProceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Pages562-567
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012 - Rome, Italy
Duration: Jun 24 2012Jun 27 2012

Other

Other2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012
CountryItaly
CityRome
Period6/24/126/27/12

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biomedical Engineering
  • Mechanical Engineering

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