Estimation system of human behaviors using a fuzzy neural network based object selection

Kiyotaka Izumi, Kohei Kamohara, Keigo Watanabe

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

2 Citations (Scopus)

Abstract

The estimation of human behaviors by robots is one of key technologies in an environment in which humans and robots coexist. In this paper, a method is proposed for promptly estimating the behavioral targets by applying a fuzzy neural network (FNN). Here, inputs to the FNN are the human velocity, the angle of the human relative to an object, and the distance between the human and an object, whereas outputs are confidences that each object among all candidates is selected to be an intended object. The resultant human behavior can be estimated as a combination of the human action estimation and the behavioral target estimation.

Original languageEnglish
Title of host publicationProceedings of SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
Pages1989-1993
Number of pages5
DOIs
Publication statusPublished - Dec 1 2008
Externally publishedYes
EventSICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology - Tokyo, Japan
Duration: Aug 20 2008Aug 22 2008

Publication series

NameProceedings of the SICE Annual Conference

Other

OtherSICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
Country/TerritoryJapan
CityTokyo
Period8/20/088/22/08

Keywords

  • Estimation of human behaviors
  • Fuzzy neural networks
  • Object estimation
  • Posture detection

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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