Image-based neural network controllers for mobile robots to track a human

Masaaki Ikeda, Hikaru Fujioka, Keigo Watanabe, Shoichi Maeyama, Isaku Nagai

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

Abstract

This paper proposes an image-based visual servoing method for human tracking by a mobile robot. Three neural networks that determine control inputs from image features are designed as controllers, where they are learned by using the genetic algorithm. We examine the network structure that is suitable as a controller for the present objective by using simulations.

Original languageEnglish
Title of host publication2015 10th Asian Control Conference: Emerging Control Techniques for a Sustainable World, ASCC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479978625
DOIs
Publication statusPublished - Sept 8 2015
Event10th Asian Control Conference, ASCC 2015 - Kota Kinabalu, Malaysia
Duration: May 31 2015Jun 3 2015

Other

Other10th Asian Control Conference, ASCC 2015
Country/TerritoryMalaysia
CityKota Kinabalu
Period5/31/156/3/15

ASJC Scopus subject areas

  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Image-based neural network controllers for mobile robots to track a human'. Together they form a unique fingerprint.

Cite this