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Learning Stable Dynamical Systems using Contraction Theory

Blocher, Caroline and Saveriano, Matteo and Lee, Dongheui (2017) Learning Stable Dynamical Systems using Contraction Theory. In: International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017. URAI, 28. Juni - 01. Juli 2017, Jeju, Korea.

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Abstract

This paper discusses the learning of robot pointto- point motions via non-linear dynamical systems and Gaussian Mixture Regression (GMR). The novelty of the proposed approach consists in guaranteeing the stability of a learned dynamical system via Contraction theory. A contraction analysis is performed to derive sufficient conditions for the global stability of a dynamical system represented by GMR. The results of this analysis are exploited to automatically compute a control input which stabilizes the learned system on-line. Simple and effective solutions are proposed to generate motion trajectories close to the demonstrated ones, without affecting the stability of the overall system. The proposed approach is evaluated on a public benchmark of point-to-point motions and compared with state-of-the-art algorithms based on Lyapunov stability theory.

Item URL in elib:https://elib.dlr.de/113325/
Document Type:Conference or Workshop Item (Speech)
Title:Learning Stable Dynamical Systems using Contraction Theory
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Blocher, CarolineTUMUNSPECIFIED
Saveriano, MatteoTUMUNSPECIFIED
Lee, DongheuiDongheui.Lee (at) dlr.dehttps://orcid.org/0000-0003-1897-7664
Date:2017
Journal or Publication Title:International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Learning contracting systems. Stable discrete movements. Learning from demonstration. Contraction theory
Event Title:URAI
Event Location:Jeju, Korea
Event Type:international Conference
Event Dates:28. Juni - 01. Juli 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben Terrestrische Assistenz-Robotik
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013)
Deposited By: Lee, Prof. Dongheui
Deposited On:31 Jul 2017 17:26
Last Modified:04 Aug 2017 10:01

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