A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. However, these approaches only focus on one single objective, i.e. path optimality, path safety, efficiency or trajectory smoothn...
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International Journal of Mechanical Engineering and Robotics Research
2023
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my.uniten.dspace-229202023-05-29T14:13:25Z A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains Khaksar W. Sahari K.S.M. 54960984900 57218170038 Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. However, these approaches only focus on one single objective, i.e. path optimality, path safety, efficiency or trajectory smoothness. In this paper, a novel parametric algorithm is proposed that is able to handle different planning goals by means of a set of objective-controller parameters. These parameters are designed carefully to cover different requirements of the path planner. Readings of the sensors will be evaluated to determine the values of four decision variables and the next position of the robot will be selected accordingly. The performance of the proposed algorithm was tested through simulation studies in different types of environments to evaluate its ability to achieve different planning goals. Simulation studies have shown the algorithm to perform robust and effective in all environments. Final 2023-05-29T06:13:25Z 2023-05-29T06:13:25Z 2016 Article 10.18178/ijmerr.5.2.115-119 2-s2.0-85006264101 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006264101&doi=10.18178%2fijmerr.5.2.115-119&partnerID=40&md5=82a3d1a1add87637a8e395c1c83cc8ac https://irepository.uniten.edu.my/handle/123456789/22920 5 2 115 119 International Journal of Mechanical Engineering and Robotics Research Scopus |
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Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. However, these approaches only focus on one single objective, i.e. path optimality, path safety, efficiency or trajectory smoothness. In this paper, a novel parametric algorithm is proposed that is able to handle different planning goals by means of a set of objective-controller parameters. These parameters are designed carefully to cover different requirements of the path planner. Readings of the sensors will be evaluated to determine the values of four decision variables and the next position of the robot will be selected accordingly. The performance of the proposed algorithm was tested through simulation studies in different types of environments to evaluate its ability to achieve different planning goals. Simulation studies have shown the algorithm to perform robust and effective in all environments. |
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54960984900 |
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54960984900 Khaksar W. Sahari K.S.M. |
| format |
Article |
| author |
Khaksar W. Sahari K.S.M. |
| spellingShingle |
Khaksar W. Sahari K.S.M. A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains |
| author_sort |
Khaksar W. |
| title |
A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains |
| title_short |
A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains |
| title_full |
A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains |
| title_fullStr |
A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains |
| title_full_unstemmed |
A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains |
| title_sort |
multi-objective parametric algorithm for sensor-based navigation in uncharted terrains |
| publisher |
International Journal of Mechanical Engineering and Robotics Research |
| publishDate |
2023 |
| _version_ |
1806426537144090624 |
| score |
13.222552 |