Mobile robot path planning using Ant Colony Optimization

Razif Rashid, N. Perumal, I. Elamvazuthi, Momen Kamal Tageldeen, M. K.A.Ahamed Khan, S. Parasuraman

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

46 Citations (Scopus)


Ant colony optimization (ACO) technique is proposed to solve the mobile robot path planning (MRPP) problem. In order to demonstrate the effectiveness of ACO in solving the MRPP problem, several maps of varying complexity used by an earlier researcher is used for evaluation. Each map consists of static obstacles in different arrangements. Besides that, each map has a grid representation with an equal number of rows and columns. The performance of the proposed ACO is tested on a given set of maps. Overall, the results demonstrate the effectiveness of the proposed approach for path planning.

Original languageEnglish
Title of host publication2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation, ROMA 2016
PublisherIEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)9781509009282
Publication statusPublished - 2017
EventIEEE International Symposium on Robotics and Manufacturing Automation 2016 - Ipoh, Malaysia
Duration: 25 Sept 201627 Sept 2016
Conference number: 2nd (Proceedings)


ConferenceIEEE International Symposium on Robotics and Manufacturing Automation 2016
Abbreviated titleROMA 2016
Internet address


  • Ant Colony Optimization
  • Mobile Robot
  • Path Planning

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