Transfer entropy for feature extraction in physical human-robot interaction: Detecting perturbations from low-cost sensors

Erik Berger, David Müller, David Vogt, Bernhard Jung, Heni Ben Amor

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

4 Scopus citations

Abstract

In physical human-robot interaction, robot behavior must be adjusted to forces applied by the human interaction partner. For measuring such forces, special-purpose sensors may be used, e.g. force-torque sensors, that are however often heavy, expensive and prone to noise. In contrast, we propose a machine learning approach for measuring external perturbations of robot behavior that uses commonly available, low-cost sensors only. During the training phase, behavior-specific statistical models of sensor measurements, so-called perturbation filters, are constructed using Principal Component Analysis, Transfer Entropy and Dynamic Mode Decomposition. During behavior execution, perturbation filters compare measured and predicted sensor values for estimating the amount and direction of forces applied by the human interaction partner. Such perturbation filters can therefore be regarded as virtual force sensors that produce continuous estimates of external forces.

Original languageEnglish (US)
Title of host publication2014 IEEE-RAS International Conference on Humanoid Robots, Humanoids 2014
PublisherIEEE Computer Society
Pages829-834
Number of pages6
ISBN (Electronic)9781479971749
DOIs
StatePublished - Feb 12 2015
Externally publishedYes
Event2014 14th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2014 - Madrid, Spain
Duration: Nov 18 2014Nov 20 2014

Publication series

NameIEEE-RAS International Conference on Humanoid Robots
Volume2015-February
ISSN (Print)2164-0572
ISSN (Electronic)2164-0580

Other

Other2014 14th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2014
CountrySpain
CityMadrid
Period11/18/1411/20/14

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Transfer entropy for feature extraction in physical human-robot interaction: Detecting perturbations from low-cost sensors'. Together they form a unique fingerprint.

Cite this