Adaptive Control for Human-Robot Skilltransfer: Trajectory Planning Based on Fluid Dynamics
Mayer, H.
Nagy, I.
Knoll, A.
Braun, E.U.
Lange, R.
Bauernschmitt, R.
Robotics & Embedded Syst., Tech. Univ. Munich;
This paper appears in: Robotics and Automation, 2007 IEEE International Conference on
Publication Date: 10-14 April 2007
On page(s): 1800-1807
Location: Roma,
ISSN: 1050-4729
ISBN: 1-4244-0601-3
INSPEC Accession Number: 9517348
Digital Object Identifier: 10.1109/ROBOT.2007.363583
Current Version Published: 2007-05-21
Abstract
A popular method for an easy and also flexible programming of robots is learning by demonstration. An intelligent controller learns a task from several examples carried out by an experienced user. Afterwards, the task can be adapted to new, formerly unknown environments. One particular challenge arising with this technique is generalization of demonstrations in order to get a generic description of the task. In this paper a new methodology for solving this problem is proposed. The main part of the algorithm exploits principles known from fluid dynamics.
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