Real-time gesture recognition for the high-level teleoperation interface of a mobile manipulator

Yerbolat Khassanov, Nursultan Imanberdiyev, Huseyin Atakan Varol

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

1 Citation (Scopus)

Abstract

This paper describes an inertial motion capture based arm gesture recognition system for the high-level control of a mobile manipulator. Left arm kinematic data of the user is acquired by an inertial motion capture system (Xsens MVN) in real-time and processed to extract supervisory user interface commands such as "Manipulator On/Off", "Base On/Off" and "Operation Pause/Resume" for a mobile manipulator system (KUKA youBot). Principal Component Analysis and Linear Discriminant Analysis are employed for dimension reduction and classification of the user kinematic data, respectively. The classification accuracy for the six class gesture recognition problem is 95.6 percent. In order to increase the reliability of the gesture recognition framework in real-time operation, a consensus voting scheme involving the last ten classification results is implemented. During the five-minute long teleoperation experiment, a total of 25 high-level commands were recognized correctly by the consensus voting enhanced gesture recognizer. The experimental subject stated that the user interface was easy to learn and did not require extensive mental effort to operate.

Original languageEnglish
Title of host publicationHRI 2014 - Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Pages204-205
Number of pages2
ISBN (Print)9781450326582
DOIs
Publication statusPublished - 2014
Event9th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2014 - Bielefeld, Germany
Duration: Mar 3 2014Mar 6 2014

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148

Other

Other9th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2014
CountryGermany
CityBielefeld
Period3/3/143/6/14

Keywords

  • Gesture recognition
  • Human-robot interaction
  • Inertial motion capture
  • Mobile manipulator
  • Teleoperation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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