Articulated robot motion planning using ant colony optimisation

Mohd Murtadha Mohamad, Nicholas K. Taylor, Mathew Walter Dunnigan

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

16 Citations (Scopus)


A new approach to robot motion planning is proposed by applying Ant Colony Optimization (ACO) with the probabilistic roadmap planner (PRM). The aim of this approach is to apply ACO to 3-dimensional robot motion planning which is complicated when involving mobile 6-dof or multiple articulated robots. An ant colony robot motion planning (ACRMP) method is proposed that has the benefit of collective behaviour of ants foraging from a nest to a food source. A number of artificial ants are released from the nest (start configuration) and begin to forage (search) towards the food (goal configuration). During the foraging process, a 1-TREE (uni-directional) searching strategy is applied in order to establish any possible connection from the nest to goal. Results from preliminary tests show that the ACRMP is capable of reducing the intermediate configuration between the initial and goal configuration in an acceptable running time.

Original languageEnglish
Title of host publication2006 3rd International IEEE Conference Intelligent Systems, Vols 1 and 2
Place of PublicationNEW YORK
Number of pages6
ISBN (Print)1424401968, 9781424401963
Publication statusPublished - 2006
Event3rd IEEE International Conference on Intelligent Systems - London
Duration: 4 Sept 20066 Sept 2006


Conference3rd IEEE International Conference on Intelligent Systems


  • Ant colony
  • Robot path planning
  • Search technique


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