MOD-RRT: A Sampling-Based Algorithm for Robot Path Planning in Dynamic Environment
This article presents an algorithm termed as multiobjective dynamic rapidly exploring random (MOD-RRT*), which is suitable for robot navigation in unknown dynamic environment. The algorithm is composed of a path generation procedure and a path replanning one. First, a modified RRT* is utilized to ob...
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| Vydáno v: | IEEE transactions on industrial electronics (1982) Ročník 68; číslo 8; s. 7244 - 7251 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
IEEE
01.08.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 0278-0046, 1557-9948 |
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| Abstract | This article presents an algorithm termed as multiobjective dynamic rapidly exploring random (MOD-RRT*), which is suitable for robot navigation in unknown dynamic environment. The algorithm is composed of a path generation procedure and a path replanning one. First, a modified RRT* is utilized to obtain an initial path, as well as generate a state tree structure as prior knowledge. Then, a shortcuting method is given to optimize the initial path. On this basis, another method is designed to replan the path if the current path is infeasible. The suggested approach can choose the best node among several candidates within a short time, where both path length and path smoothness are considered. Comparing with other static planning algorithms, the MOD-RRT* can generate a higher quality initial path. Simulations on the dynamic environment are conducted to clarify the efficient performance of our algorithm in avoiding unknown obstacles. Furthermore, real applicative experiment further proves the effectiveness of our approach in practical applications. |
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| AbstractList | This article presents an algorithm termed as multiobjective dynamic rapidly exploring random (MOD-RRT*), which is suitable for robot navigation in unknown dynamic environment. The algorithm is composed of a path generation procedure and a path replanning one. First, a modified RRT* is utilized to obtain an initial path, as well as generate a state tree structure as prior knowledge. Then, a shortcuting method is given to optimize the initial path. On this basis, another method is designed to replan the path if the current path is infeasible. The suggested approach can choose the best node among several candidates within a short time, where both path length and path smoothness are considered. Comparing with other static planning algorithms, the MOD-RRT* can generate a higher quality initial path. Simulations on the dynamic environment are conducted to clarify the efficient performance of our algorithm in avoiding unknown obstacles. Furthermore, real applicative experiment further proves the effectiveness of our approach in practical applications. |
| Author | Sun, Haixin Qi, Jie Yang, Hui |
| Author_xml | – sequence: 1 givenname: Jie orcidid: 0000-0001-5376-1514 surname: Qi fullname: Qi, Jie email: qijie@xmu.edu.cn organization: College of Electronic Science and Technology, Xiamen University, Xiamen, China – sequence: 2 givenname: Hui orcidid: 0000-0002-8635-6707 surname: Yang fullname: Yang, Hui email: hyang@stu.xmu.edu.cn organization: College of Electronic Science and Technology, Xiamen University, Xiamen, China – sequence: 3 givenname: Haixin orcidid: 0000-0001-8249-1197 surname: Sun fullname: Sun, Haixin email: hxsun@xmu.edu.cn organization: School of Informatics, Xiamen University, Xiamen, China |
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| SubjectTerms | Algorithms Autonomous mobile robot Collision avoidance dynamic path planning Heuristic algorithms Mobile robots multiobjective planning Path planning Planning Probabilistic logic rapidly exploring random tree (RRT) Robots Smoothness |
| Title | MOD-RRT: A Sampling-Based Algorithm for Robot Path Planning in Dynamic Environment |
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