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Mobile robot path planning using Ant Colony Optimization

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

Year
2016
Citations
48

Abstract

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.

Keywords

Ant colony optimization algorithmsMotion planningMobile robotPath (computing)Computer scienceSet (abstract data type)Artificial intelligenceGridRepresentation (politics)Robot

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