Obstacle recognition for path planning in autonomous mobile robots

Ulises Orozco-Rosas, Kenia Picos, Oscar Montiel, Roberto Sepúlveda, Víctor H. Díaz-Ramírez

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

4 Scopus citations

Abstract

Computer vision is an important task in robotics applications. This work proposes an approach for autonomous mobile robot navigation using the integration of the template-matching filters for obstacle detection and the evolutionary artificial potential field method for path planning. The recognition system employs a digital camera to sense the environment of a mobile robot. The captured scene is processed by a bank of space variant filters in order to find the obstacles and a feasible area for the robot navigation. The path planning employs evolutionary artificial potential fields to derive optimal potential field functions using evolutionary computation. Simulation results to validate the analysis and implementation are provided; they were specifically made to show the efiectiveness and the eficiency of the proposal.

Original languageEnglish
Title of host publicationOptics and Photonics for Information Processing X
EditorsKhan M. Iftekharuddin, Andres Marquez, Mohammad A. Matin, Abdul A. S. Awwal, Mireya Garcia Vazquez
PublisherSPIE
ISBN (Electronic)9781510603318
DOIs
StatePublished - 2016
Event10th Conference on Optics and Photonics for Information Processing - San Diego, United States
Duration: 29 Aug 201630 Aug 2016

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9970
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference10th Conference on Optics and Photonics for Information Processing
Country/TerritoryUnited States
CitySan Diego
Period29/08/1630/08/16

Keywords

  • Object recognition
  • evolutionary artificial potential field
  • mobile robots
  • path planning
  • template matching

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