Dynamic attack motion prediction for kendo agent

Yasufumi Tanaka, Kazuhiro Kosuge

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

3 Citations (Scopus)

Abstract

A motion prediction method using Gaussian Mixture Models (GMM) is applied to a kendo agent (Kendo is a traditional Japanese martial art). Human player motion is measured by a motion capture system, using markers attached to each of the player's joints. Measurement information is converted to a state vector with Euler angles to indicate orientation of the sword and orientation of each part of the player's body. To model the motion as a nonlinear dynamical system, GMMs are generated from a demonstration set when an opponent is attacked. The efficiency of the proposed method is experimentally verified.

Original languageEnglish
Title of host publicationIROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2187-2193
Number of pages7
ISBN (Electronic)9781479969340
DOIs
Publication statusPublished - 2014 Oct 31
Event2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 - Chicago, United States
Duration: 2014 Sep 142014 Sep 18

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Other

Other2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
CountryUnited States
CityChicago
Period14/9/1414/9/18

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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