People following behaviour in an industrial enviroment using laser and stereo camera

  • J. M. Martínez-Otzeta
  • , A. Ibarguren
  • , A. Ansuategi
  • , C. Tubío
  • , J. Aristondo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Mobile robots have a large application potential in industrial shop floors, improving the human action in this kind of environments. The productivity can be greatly increased while reducing cost, particularly for surface operations such as material transport, survey and sampling. In this paper a system able to follow a worker in an industrial environment based on information provided by a laser scan and a stereo camera is presented. In order to accomplish this goal, a probabilistic approach for human leg detection based on data provided by a laser scan is used, enhanced with an histogram based depth detector. The proposed approach also integrates tracking techniques as Kalman Filters to endow the system with an error recovering tool to be used in a real environment.

Original languageEnglish
Title of host publicationTrends in Applied Intelligent Systems - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Proceedings
Pages508-517
Number of pages10
EditionPART 3
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2010 - Cordoba, Spain
Duration: 1 Jun 20104 Jun 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume6098 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2010
Country/TerritorySpain
CityCordoba
Period1/06/104/06/10

Keywords

  • human-robot interaction
  • Mobile robotics
  • sensor fusion

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