Dynamic Mode Decomposition for perturbation estimation in human robot interaction

Erik Berger, Mark Sastuba, David Vogt, Bernhard Jung, Hani Ben Amor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

In many settings, e.g. physical human-robot interaction, robotic behavior must be made robust against more or less spontaneous application of external forces. Typically, this problem is tackled by means of special purpose force sensors which are, however, not available on many robotic platforms. In contrast, we propose a machine learning approach suitable for more common, although often noisy sensors. This machine learning approach makes use of Dynamic Mode Decomposition (DMD) which is able to extract the dynamics of a nonlinear system. It is therefore well suited to separate noise from regular oscillations in sensor readings during cyclic robot movements under different behavior configurations. We demonstrate the feasibility of our approach with an example where physical forces are exerted on a humanoid robot during walking. In a training phase, a snapshot based DMD model for behavior specific parameter configurations is learned. During task execution the robot must detect and estimate the external forces exerted by a human interaction partner. We compare the DMD-based approach to other interpolation schemes and show that the former outperforms the latter particularly in the presence of sensor noise. We conclude that DMD which has so far been mostly used in other fields of science, particularly fluid mechanics, is also a highly promising method for robotics.

Original languageEnglish (US)
Title of host publicationIEEE RO-MAN 2014 - 23rd IEEE International Symposium on Robot and Human Interactive Communication: Human-Robot Co-Existence: Adaptive Interfaces and Systems for Daily Life, Therapy, Assistance and Socially Engaging Interactions
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages593-600
Number of pages8
ISBN (Print)9781479967636
DOIs
StatePublished - Oct 15 2014
Externally publishedYes
Event23rd IEEE International Symposium on Robot and Human Interactive Communication, IEEE RO-MAN 2014 - Edinburgh, United Kingdom
Duration: Aug 25 2014Aug 29 2014

Other

Other23rd IEEE International Symposium on Robot and Human Interactive Communication, IEEE RO-MAN 2014
CountryUnited Kingdom
CityEdinburgh
Period8/25/148/29/14

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction

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