On correction prediction in man and robot using the cerebellar model articulation controller

Master thesis (2019)

Authors

J.K. van Duijneveldt Mechanical Engineering

Contributors

P.P. Jonker Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering (supervisor 1)
M. Wisse Robot Dynamics - Mechanical, Maritime and Materials Engineering (supervisor 2)
H. Vallery Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering (supervisor 2)
Faculty
Mechanical Engineering
Copyright: © 2019 Joris van Duijneveldt
More Info
expand_more

Published Date

26-09-2019

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical Engineering

Abstract

The subject of this thesis is to investigate whether the Cerebellar Model Articulation Controller (CMAC) can be used to anticipate controller corrections and increase performance by reducing delays in humanoid robots. This question can be divided into two subquestions. Firstly, whether the CMAC is a suitable architecture for the prediction of controller actions for a humanoid soccer robot. Using a 2D model of a robotic leg, the results of this thesis show that the CMAC can indeed learn to anticipate a corrective control signal 30 ms ahead. Secondly, whether the architecture of the aforementioned setup can increase the performance of adequately passing a ball by reducing delays. The experiments show that the use of a CMAC can increase the performance of the robotic setup.