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Front. Robot. AI | doi: 10.3389/frobt.2019.00063

Adaptivity of End Effector Motor Control Under Different Sensory Conditions: Experiments with Humans in Virtual Reality and Robotic Applications

  • 1University of Bremen, Germany

The investigation of human perception and movement kinematics during manipulation tasks provides insights that can be applied in the design of robotic systems in order to perform human-like manipulations in different contexts and with different performance requirements. In this paper we investigate control in a motor task, in which a tool is moved vertically until it touches a support surface. We evaluate how acoustic and haptic sensory information generated at the moment of contact modulates the kinematic parameters of the movement. Experimental results show differences in the achieved motor control precision and adaptation rate across conditions. We describe how the experimental results can be used in robotics applications in the fields of unsupervised learning, supervised learning from human demonstrators and teleoperations.

Keywords: contact velocity, motor control, motor learning, robot learning, Hidden Markov (HMM)

Received: 20 Mar 2019; Accepted: 10 Jul 2019.

Edited by:

Helge Ritter, Bielefeld University, Germany

Reviewed by:

Claudia Casellato, University of Pavia, Italy
Anat Dahan, Technion Israel Institute of Technology, Israel  

Copyright: © 2019 Maldonado Cañon, Kluss and Zetzsche. 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: Mx. Jaime L. Maldonado Cañon, University of Bremen, Bremen, Germany,