Path planning for a mobile robot using ant colony optimization and the influence of critical obstacle

Jihee Han, Hyungjune Park, Yoon Ho Seo

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

10 Citations (Scopus)


Path planning in mobile robots is important since its performance can significantly affect the utilization of robots. Thus we propose a methodology, ACOIC (Ant colony optimization with the influence of critical obstacle), that utilizes the influence values propagated by critical obstacles as the initial pheromones and initial transition probabilities in ACO. Through this approach, we can enhance the traditional ACO by leading ants toward the preferable direction rather than considering all directions in the same weight. Thus the ants are able to reach the goal efficiently without wandering the regions since the optimal path can be obtained proximal to the critical obstacles. In experiment, we implemented the ACOIC and ACO in 3 different maps in terms of the number and shape of the obstacles in order to see if any differences in performance between those two methods exist. As a result, ACOIC was more capable than ACO for generating an optimal path efficiently.

Original languageEnglish
Title of host publication6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016
PublisherIEOM Society
Number of pages9
ISBN (Print)9780985549749, 9780985549756
Publication statusPublished - 2016
EventIEOM Detroit Conference, IEOM 2016 - Southfield, United States
Duration: 2016 Sept 232016 Sept 25


OtherIEOM Detroit Conference, IEOM 2016
Country/TerritoryUnited States


  • Ant colony optimization
  • Influence propagation
  • Meta-heuristics
  • Path planning

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering


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