Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm
Mobile robots are becoming more and more widely used in industry and life, so the navigation of robots in dynamic environments has become an urgent problem to be solved. Dynamic path planning has, therefore, received more attention. This paper proposes a real-time dynamic path planning method for mo...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/1/188 |
| _version_ | 1818037331978878976 |
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| author | Qing Wu Zeyu Chen Lei Wang Hao Lin Zijing Jiang Shuai Li Dechao Chen |
| author_facet | Qing Wu Zeyu Chen Lei Wang Hao Lin Zijing Jiang Shuai Li Dechao Chen |
| author_sort | Qing Wu |
| collection | DOAJ |
| description | Mobile robots are becoming more and more widely used in industry and life, so the navigation of robots in dynamic environments has become an urgent problem to be solved. Dynamic path planning has, therefore, received more attention. This paper proposes a real-time dynamic path planning method for mobile robots that can avoid both static and dynamic obstacles. The proposed intelligent optimization method can not only get a better path but also has outstanding advantages in planning time. The algorithm used in the proposed method is a hybrid algorithm based on the beetle antennae search (BAS) algorithm and the artificial potential field (APF) algorithm, termed the BAS-APF method. By establishing a potential field, the convergence speed is accelerated, and the defect that the APF is easily trapped in the local minimum value is also avoided. At the same time, by setting a security scope to make the path closer to the available path in the real environment, the effectiveness and superiority of the proposed method are verified through simulative results. |
| first_indexed | 2024-12-10T07:25:09Z |
| format | Article |
| id | doaj.art-96bc7660bd624e90800d837c2ba9ad33 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-12-10T07:25:09Z |
| publishDate | 2019-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-96bc7660bd624e90800d837c2ba9ad332022-12-22T01:57:42ZengMDPI AGSensors1424-82202019-12-0120118810.3390/s20010188s20010188Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization AlgorithmQing Wu0Zeyu Chen1Lei Wang2Hao Lin3Zijing Jiang4Shuai Li5Dechao Chen6School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, ChinaSchool of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, ChinaSchool of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, ChinaSchool of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, ChinaSchool of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, ChinaDepartment of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong 999077, ChinaSchool of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, ChinaMobile robots are becoming more and more widely used in industry and life, so the navigation of robots in dynamic environments has become an urgent problem to be solved. Dynamic path planning has, therefore, received more attention. This paper proposes a real-time dynamic path planning method for mobile robots that can avoid both static and dynamic obstacles. The proposed intelligent optimization method can not only get a better path but also has outstanding advantages in planning time. The algorithm used in the proposed method is a hybrid algorithm based on the beetle antennae search (BAS) algorithm and the artificial potential field (APF) algorithm, termed the BAS-APF method. By establishing a potential field, the convergence speed is accelerated, and the defect that the APF is easily trapped in the local minimum value is also avoided. At the same time, by setting a security scope to make the path closer to the available path in the real environment, the effectiveness and superiority of the proposed method are verified through simulative results.https://www.mdpi.com/1424-8220/20/1/188hybrid optimization algorithmmobile robotreal-time path planningdynamic obstacle avoidancebeetle antennae search algorithm (bas) |
| spellingShingle | Qing Wu Zeyu Chen Lei Wang Hao Lin Zijing Jiang Shuai Li Dechao Chen Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm Sensors hybrid optimization algorithm mobile robot real-time path planning dynamic obstacle avoidance beetle antennae search algorithm (bas) |
| title | Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm |
| title_full | Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm |
| title_fullStr | Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm |
| title_full_unstemmed | Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm |
| title_short | Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm |
| title_sort | real time dynamic path planning of mobile robots a novel hybrid heuristic optimization algorithm |
| topic | hybrid optimization algorithm mobile robot real-time path planning dynamic obstacle avoidance beetle antennae search algorithm (bas) |
| url | https://www.mdpi.com/1424-8220/20/1/188 |
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