Using learning from demonstration to generate real-time guidance for haptic shared control

Conference paper (2016)

Authors

C. J. Perez-Del-Pulgar European Space Agency (ESA), Universidad de Málaga

J. Smisek European Space Agency (ESA),

V. F. Munoz Universidad de Málaga

A. Schiele European Space Agency (ESA), Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering

To reference this document use:

http://resolver.tudelft.nl/uuid:390a5cf9-382d-42f3-a905-0c950cb1ed8c

More Info

expand_more

Published Date

2016

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.

Abstract

This paper introduces a new Learning from Demonstration (LfD)-based method that makes usage of robot effector forces and torques recorded during expert demonstrations, to generate force-based haptic guidance reference trajectories on-line, that are intended to be used during haptic shared control for additional operator 'guidance'. Derived haptic guidance trajectories are superimposed to master-device inputs and feedback forces within a bilateral control experiment, to assist an operator by the guidance during peg-in-hole insertion. We show that 96 peg-in-hole expert demonstrations were sufficient to obtain a good model of the task, which was used on-line to generate haptic guidance trajectories in real-time with a 1kHz sampling rate.