Hybrid rule-based motion planner for mobile robot in cluttered workspace A combination of RRT and cell decomposition approaches
Motion planning problem is an active field in robotics. It is concerned with converting high-level task specifications into low-level descriptions of how to move and provides a feasible sequence of movements that avoid obstacles while respecting kinematic and dynamic equations. In this work, new pla...
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| Veröffentlicht in: | Soft computing (Berlin, Germany) Jg. 22; H. 6; S. 1815 - 1831 |
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| Sprache: | Englisch |
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01.03.2018
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| ISSN: | 1432-7643, 1433-7479 |
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| Abstract | Motion planning problem is an active field in robotics. It is concerned with converting high-level task specifications into low-level descriptions of how to move and provides a feasible sequence of movements that avoid obstacles while respecting kinematic and dynamic equations. In this work, new planners are designed with the aim of developing an efficient motion planner in a heterogeneous, cluttered, and dynamic workspace. The planners are composed of two layers, and they use a rule-based system as a guidance. The first layer uses exact cell decomposition method, which divides the workspace into manageable regions and finds the adjacency information for them. The second layer utilizes rapidly exploring random tree algorithm RRT that finds a solution in a cluttered workspace. The adjacency information of the free cells and the exploration information that is provided by RRT are combined and utilized to help the planners classifying the free regions and guiding the growth of RRT trees efficiently toward the most important areas. Two types of the planners are proposed, the first one uses adviser that pulls the trees’ growth toward the boundary areas between explored and unexplored regions, while the adviser of the second planner uses the collision information and fuzzy rules to guide the trees’ growth toward areas that have low collision rate around the boundaries of explored regions. The planners are tested in stationary as well as in changed workspace. The proposed methods have been compared to other approaches and the simulation results show that they yield better results in terms of completeness and efficiency. |
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| AbstractList | Motion planning problem is an active field in robotics. It is concerned with converting high-level task specifications into low-level descriptions of how to move and provides a feasible sequence of movements that avoid obstacles while respecting kinematic and dynamic equations. In this work, new planners are designed with the aim of developing an efficient motion planner in a heterogeneous, cluttered, and dynamic workspace. The planners are composed of two layers, and they use a rule-based system as a guidance. The first layer uses exact cell decomposition method, which divides the workspace into manageable regions and finds the adjacency information for them. The second layer utilizes rapidly exploring random tree algorithm RRT that finds a solution in a cluttered workspace. The adjacency information of the free cells and the exploration information that is provided by RRT are combined and utilized to help the planners classifying the free regions and guiding the growth of RRT trees efficiently toward the most important areas. Two types of the planners are proposed, the first one uses adviser that pulls the trees’ growth toward the boundary areas between explored and unexplored regions, while the adviser of the second planner uses the collision information and fuzzy rules to guide the trees’ growth toward areas that have low collision rate around the boundaries of explored regions. The planners are tested in stationary as well as in changed workspace. The proposed methods have been compared to other approaches and the simulation results show that they yield better results in terms of completeness and efficiency. |
| Author | Matousek, Radomil Abbadi, Ahmad |
| Author_xml | – sequence: 1 givenname: Ahmad orcidid: 0000-0002-6514-916X surname: Abbadi fullname: Abbadi, Ahmad email: Ahmad.Abbadi@mail.com organization: Department of Information Technologies, Faculty of Informatics, Masaryk University, Department of Applied Computer Science, Faculty of Mechanical Engineering, Brno University of Technology – sequence: 2 givenname: Radomil surname: Matousek fullname: Matousek, Radomil organization: Department of Applied Computer Science, Faculty of Mechanical Engineering, Brno University of Technology |
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| CitedBy_id | crossref_primary_10_1109_ACCESS_2019_2908100 crossref_primary_10_1016_j_jestch_2023_101343 crossref_primary_10_1177_09544054221130386 crossref_primary_10_1109_ACCESS_2025_3579863 crossref_primary_10_1109_ACCESS_2025_3536383 crossref_primary_10_1016_j_robot_2019_02_013 |
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| Keywords | Motion planning Cell decomposition Sampling-based planner Adaptive sampling RRT Guided planner Path planning Rule-based |
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| SubjectTerms | Artificial Intelligence Computational Intelligence Control Engineering Mathematical Logic and Foundations Mechatronics Methodologies and Application Robotics |
| Subtitle | A combination of RRT and cell decomposition approaches |
| Title | Hybrid rule-based motion planner for mobile robot in cluttered workspace |
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