Mobile robot path planning using hybrid genetic algorithm and traversability vectors method
The shortest/optimal path generation is essential for the efficient operation of a mobile robot. Recent advances in robotics and machine intelligence have led to the application of modern optimization method such as the genetic algorithm (GA), to solve the path-planning problem. However, the genetic...
| Main Authors: | , , , |
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| Format: | Article |
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2004
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| Online Access: | http://shdl.mmu.edu.my/2515/ |
| _version_ | 1848790076447784960 |
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| author | Loo, , CK Rao, , MVC Wong,, EK Rajeswari, ,M |
| author_facet | Loo, , CK Rao, , MVC Wong,, EK Rajeswari, ,M |
| author_sort | Loo, , CK |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | The shortest/optimal path generation is essential for the efficient operation of a mobile robot. Recent advances in robotics and machine intelligence have led to the application of modern optimization method such as the genetic algorithm (GA), to solve the path-planning problem. However, the genetic algorithm path planning approach in the previous works requires a preprocessing step that captures the connectivity of the free-space in a concise representation. In this paper, GA path-planning approach is enhanced with feasible path detection mechanism based on traversability vectors method. This novel idea eliminates the need of free-space connectivity representation. The feasible path detection is performed concurrently while the GA performs the search for the shortest path. The performance of the proposed GA approach is tested on three different environments consisting of polygonal obstacles with increasing complexity. In all experiments, the GA has successfully detected the near-optimal feasible travelling path for mobile. |
| first_indexed | 2025-11-14T18:06:52Z |
| format | Article |
| id | mmu-2515 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:06:52Z |
| publishDate | 2004 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-25152011-08-22T06:53:15Z http://shdl.mmu.edu.my/2515/ Mobile robot path planning using hybrid genetic algorithm and traversability vectors method Loo, , CK Rao, , MVC Wong,, EK Rajeswari, ,M QA75.5-76.95 Electronic computers. Computer science The shortest/optimal path generation is essential for the efficient operation of a mobile robot. Recent advances in robotics and machine intelligence have led to the application of modern optimization method such as the genetic algorithm (GA), to solve the path-planning problem. However, the genetic algorithm path planning approach in the previous works requires a preprocessing step that captures the connectivity of the free-space in a concise representation. In this paper, GA path-planning approach is enhanced with feasible path detection mechanism based on traversability vectors method. This novel idea eliminates the need of free-space connectivity representation. The feasible path detection is performed concurrently while the GA performs the search for the shortest path. The performance of the proposed GA approach is tested on three different environments consisting of polygonal obstacles with increasing complexity. In all experiments, the GA has successfully detected the near-optimal feasible travelling path for mobile. 2004 Article NonPeerReviewed Loo, , CK and Rao, , MVC and Wong,, EK and Rajeswari, ,M (2004) Mobile robot path planning using hybrid genetic algorithm and traversability vectors method. INTELLIGENT AUTOMATION AND SOFT COMPUTING, 10 (1). pp. 51-63. ISSN 1079-8587 |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Loo, , CK Rao, , MVC Wong,, EK Rajeswari, ,M Mobile robot path planning using hybrid genetic algorithm and traversability vectors method |
| title | Mobile robot path planning using hybrid genetic algorithm and traversability vectors method |
| title_full | Mobile robot path planning using hybrid genetic algorithm and traversability vectors method |
| title_fullStr | Mobile robot path planning using hybrid genetic algorithm and traversability vectors method |
| title_full_unstemmed | Mobile robot path planning using hybrid genetic algorithm and traversability vectors method |
| title_short | Mobile robot path planning using hybrid genetic algorithm and traversability vectors method |
| title_sort | mobile robot path planning using hybrid genetic algorithm and traversability vectors method |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://shdl.mmu.edu.my/2515/ |