Mobile robot path planning using Ant Colony Optimization

Rashid, R. and Perumal, N. and Elamvazuthi, I. and Tageldeen, M.K. and Khan, M.K.A.A. and Parasuraman, S. (2017) Mobile robot path planning using Ant Colony Optimization. In: UNSPECIFIED.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

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. © 2016 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 44; Conference of 2nd IEEE International Symposium on Robotics and Manufacturing Automation, ROMA 2016 ; Conference Date: 25 September 2016 Through 27 September 2016; Conference Code:126431
Uncontrolled Keywords: Artificial intelligence; Manufacture; Mobile robots; Motion planning; Robot programming; Robotics; Robots, Ant Colony Optimization (ACO); Robot path-planning; Static obstacles, Ant colony optimization
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:20
Last Modified: 09 Nov 2023 16:20
URI: https://khub.utp.edu.my/scholars/id/eprint/8845

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