Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system
Despite the proven advantages of sampling-based motion planning algorithms, their inability to handle online navigation tasks and providing low-cost solutions make them less efficient in practice. In this paper, a novel sampling-based algorithm is proposed which is able to plan in an unknown environ...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Published: |
Springer
2019
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/87523/ |
| _version_ | 1848860451165700096 |
|---|---|
| author | Khaksar, Weria Tang, Sai Hong Mohamed Sahari, Khairul Salleh Khaksar, Mansoor Toressen, Jim |
| author_facet | Khaksar, Weria Tang, Sai Hong Mohamed Sahari, Khairul Salleh Khaksar, Mansoor Toressen, Jim |
| author_sort | Khaksar, Weria |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Despite the proven advantages of sampling-based motion planning algorithms, their inability to handle online navigation tasks and providing low-cost solutions make them less efficient in practice. In this paper, a novel sampling-based algorithm is proposed which is able to plan in an unknown environment and provides solutions with lower cost in terms of path length, runtime and stability of the results. First, a fuzzy controller is designed which incorporates the heuristic rules of Tabu search to enable the planner for solving online navigation tasks. Then, an adaptive neuro-fuzzy inference system (ANFIS) is proposed such that it constructs and optimizes the fuzzy controller based on a set of given input/output data. Furthermore, a heuristic dataset generator is implemented to provide enough data for the ANFIS using a randomized procedure. The performance of the proposed algorithm is evaluated through simulation in different motion planning queries. Finally, the proposed planner is compared to some of the similar motion planning algorithms to support the claim of superiority of its performance. |
| first_indexed | 2025-11-15T12:45:26Z |
| format | Article |
| id | upm-87523 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T12:45:26Z |
| publishDate | 2019 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-875232023-05-17T03:24:40Z http://psasir.upm.edu.my/id/eprint/87523/ Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system Khaksar, Weria Tang, Sai Hong Mohamed Sahari, Khairul Salleh Khaksar, Mansoor Toressen, Jim Despite the proven advantages of sampling-based motion planning algorithms, their inability to handle online navigation tasks and providing low-cost solutions make them less efficient in practice. In this paper, a novel sampling-based algorithm is proposed which is able to plan in an unknown environment and provides solutions with lower cost in terms of path length, runtime and stability of the results. First, a fuzzy controller is designed which incorporates the heuristic rules of Tabu search to enable the planner for solving online navigation tasks. Then, an adaptive neuro-fuzzy inference system (ANFIS) is proposed such that it constructs and optimizes the fuzzy controller based on a set of given input/output data. Furthermore, a heuristic dataset generator is implemented to provide enough data for the ANFIS using a randomized procedure. The performance of the proposed algorithm is evaluated through simulation in different motion planning queries. Finally, the proposed planner is compared to some of the similar motion planning algorithms to support the claim of superiority of its performance. Springer 2019 Article PeerReviewed Khaksar, Weria and Tang, Sai Hong and Mohamed Sahari, Khairul Salleh and Khaksar, Mansoor and Toressen, Jim (2019) Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system. Neural Computing and Applications, 31. 1275 - 1289. ISSN 0941-0643; ESSN: 1433-3058 https://link.springer.com/article/10.1007/s00521-017-3069-6 10.1007/s00521-017-3069-6 |
| spellingShingle | Khaksar, Weria Tang, Sai Hong Mohamed Sahari, Khairul Salleh Khaksar, Mansoor Toressen, Jim Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system |
| title | Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system |
| title_full | Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system |
| title_fullStr | Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system |
| title_full_unstemmed | Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system |
| title_short | Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system |
| title_sort | sampling-based online motion planning for mobile robots: utilization of tabu search and adaptive neuro-fuzzy inference system |
| url | http://psasir.upm.edu.my/id/eprint/87523/ http://psasir.upm.edu.my/id/eprint/87523/ http://psasir.upm.edu.my/id/eprint/87523/ |