Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus
Learning is a complex cognitive process; thus, the algorithms that can simulate learning are also complex. The complexity is due to the fact that little is known about the learning process that can be simulated in a machine. In this study two methods have been chosen to navigate a simulated robot to...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Research Management Institute (RMI)
2009
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| Online Access: | https://ir.uitm.edu.my/id/eprint/12917/ |
| _version_ | 1848803200590675968 |
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| author | Abu Bakar, Nordin Abdul Kudus, Rosnawati |
| author_facet | Abu Bakar, Nordin Abdul Kudus, Rosnawati |
| author_sort | Abu Bakar, Nordin |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | Learning is a complex cognitive process; thus, the algorithms that can simulate learning are also complex. The complexity is due to the fact that little is known about the learning process that can be simulated in a machine. In this study two methods have been chosen to navigate a simulated robot to a target point; namely, Ants Colony Optimisation (ACO) and the Fuzzy Approach. The focus
of this paper is primarily the ACO method and the Fuzzy Approach is used as a comparative benchmark. Three scenarios were designed: the Big Hall, the Wall Following and the Volcano Challenge. These experimental scenarios
represent the respective navigation frameworks found in the literature used to test learning algorithms. The results indicate that the ACO’s performance is inferior to the Fuzzy approach; justification for this has been discussed in
relation to previous research in this area. Some future work to investigate this phenomenon further and improve the performance of the ACO algorithm is also presented. |
| first_indexed | 2025-11-14T21:35:28Z |
| format | Article |
| id | uitm-12917 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:35:28Z |
| publishDate | 2009 |
| publisher | Research Management Institute (RMI) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-129172016-05-27T11:17:34Z https://ir.uitm.edu.my/id/eprint/12917/ Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus srj Abu Bakar, Nordin Abdul Kudus, Rosnawati Machine learning Fuzzy arithmetic Computer simulation Learning is a complex cognitive process; thus, the algorithms that can simulate learning are also complex. The complexity is due to the fact that little is known about the learning process that can be simulated in a machine. In this study two methods have been chosen to navigate a simulated robot to a target point; namely, Ants Colony Optimisation (ACO) and the Fuzzy Approach. The focus of this paper is primarily the ACO method and the Fuzzy Approach is used as a comparative benchmark. Three scenarios were designed: the Big Hall, the Wall Following and the Volcano Challenge. These experimental scenarios represent the respective navigation frameworks found in the literature used to test learning algorithms. The results indicate that the ACO’s performance is inferior to the Fuzzy approach; justification for this has been discussed in relation to previous research in this area. Some future work to investigate this phenomenon further and improve the performance of the ACO algorithm is also presented. Research Management Institute (RMI) 2009 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/12917/1/AJ_NORDIN%20ABU%20BAKAR%20SRJ%2009%201.pdf Abu Bakar, Nordin and Abdul Kudus, Rosnawati (2009) Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus. (2009) Scientific Research Journal <https://ir.uitm.edu.my/view/publication/Scientific_Research_Journal.html>, 6 (1). pp. 65-76. ISSN 1675-7009 https://srj.uitm.edu.my/ |
| spellingShingle | Machine learning Fuzzy arithmetic Computer simulation Abu Bakar, Nordin Abdul Kudus, Rosnawati Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus |
| title | Solving robot path planning problem using Ant Colony
Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus |
| title_full | Solving robot path planning problem using Ant Colony
Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus |
| title_fullStr | Solving robot path planning problem using Ant Colony
Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus |
| title_full_unstemmed | Solving robot path planning problem using Ant Colony
Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus |
| title_short | Solving robot path planning problem using Ant Colony
Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus |
| title_sort | solving robot path planning problem using ant colony
optimisation (aco) approach / nordin abu bakar and rosnawati abdul kudus |
| topic | Machine learning Fuzzy arithmetic Computer simulation |
| url | https://ir.uitm.edu.my/id/eprint/12917/ https://ir.uitm.edu.my/id/eprint/12917/ |