A Novel Online Path Planning Algorithm for Multi-Robots Based on the Secondary Immune Response in Dynamic Environments
To solve the online path planning of multi-robots in dynamic environments, a novel secondary immune responses-based immune path planning algorithm (SIRIPPA) is presented. The algorithm comprises two immune stages. In the primary immune stage, the antibodies are mainly designed for obstacle avoidance...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/13/3/562 |
| _version_ | 1797318846164500480 |
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| author | Yafeng Jiang Liang Zhang Mingxin Yuan Yi Shen |
| author_facet | Yafeng Jiang Liang Zhang Mingxin Yuan Yi Shen |
| author_sort | Yafeng Jiang |
| collection | DOAJ |
| description | To solve the online path planning of multi-robots in dynamic environments, a novel secondary immune responses-based immune path planning algorithm (SIRIPPA) is presented. The algorithm comprises two immune stages. In the primary immune stage, the antibodies are mainly designed for obstacle avoidance and a primary immune kinetic model is designed in terms of the different impacts of obstacles on robot behaviors. The primary immune antibodies and their concentration values are mainly taken as the prior knowledge to accelerate the secondary immune response. In the secondary immune stage, aiming at the same obstacle antigens, which invade once more, the immune system quickly produces many behavior antibodies. Combining the primary immune results and secondary immune response results, the path planning performance of multi-robots is improved. The simulation experiment indicates that, in static environment tests, compared to corresponding immune planning algorithms, the SIRIPPA exhibits an average reduction of 6.22% in the global path length, a decrease of 23.00% in the average smoothness, and an average energy consumption reduction of 27.55%; the algorithm exhibits a better performance for path planning. The simulation test in a dynamic environment shows the good flexibility and stability of the SIRIPPA. Additionally, the experimental results in a real environment further support the validity of the SIRIPPA. |
| first_indexed | 2024-03-08T03:58:19Z |
| format | Article |
| id | doaj.art-12418688de6b47909be496d6cc3c840e |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-08T03:58:19Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-12418688de6b47909be496d6cc3c840e2024-02-09T15:10:38ZengMDPI AGElectronics2079-92922024-01-0113356210.3390/electronics13030562A Novel Online Path Planning Algorithm for Multi-Robots Based on the Secondary Immune Response in Dynamic EnvironmentsYafeng Jiang0Liang Zhang1Mingxin Yuan2Yi Shen3School of Mechatronics and Power Engineering, Jiangsu University of Science and Technology, Zhangjiagang 215600, ChinaSchool of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212000, ChinaSchool of Mechatronics and Power Engineering, Jiangsu University of Science and Technology, Zhangjiagang 215600, ChinaSchool of Mechatronics and Power Engineering, Jiangsu University of Science and Technology, Zhangjiagang 215600, ChinaTo solve the online path planning of multi-robots in dynamic environments, a novel secondary immune responses-based immune path planning algorithm (SIRIPPA) is presented. The algorithm comprises two immune stages. In the primary immune stage, the antibodies are mainly designed for obstacle avoidance and a primary immune kinetic model is designed in terms of the different impacts of obstacles on robot behaviors. The primary immune antibodies and their concentration values are mainly taken as the prior knowledge to accelerate the secondary immune response. In the secondary immune stage, aiming at the same obstacle antigens, which invade once more, the immune system quickly produces many behavior antibodies. Combining the primary immune results and secondary immune response results, the path planning performance of multi-robots is improved. The simulation experiment indicates that, in static environment tests, compared to corresponding immune planning algorithms, the SIRIPPA exhibits an average reduction of 6.22% in the global path length, a decrease of 23.00% in the average smoothness, and an average energy consumption reduction of 27.55%; the algorithm exhibits a better performance for path planning. The simulation test in a dynamic environment shows the good flexibility and stability of the SIRIPPA. Additionally, the experimental results in a real environment further support the validity of the SIRIPPA.https://www.mdpi.com/2079-9292/13/3/562multi-robotspath planningimmune networksecondary immune responsedynamic environment |
| spellingShingle | Yafeng Jiang Liang Zhang Mingxin Yuan Yi Shen A Novel Online Path Planning Algorithm for Multi-Robots Based on the Secondary Immune Response in Dynamic Environments Electronics multi-robots path planning immune network secondary immune response dynamic environment |
| title | A Novel Online Path Planning Algorithm for Multi-Robots Based on the Secondary Immune Response in Dynamic Environments |
| title_full | A Novel Online Path Planning Algorithm for Multi-Robots Based on the Secondary Immune Response in Dynamic Environments |
| title_fullStr | A Novel Online Path Planning Algorithm for Multi-Robots Based on the Secondary Immune Response in Dynamic Environments |
| title_full_unstemmed | A Novel Online Path Planning Algorithm for Multi-Robots Based on the Secondary Immune Response in Dynamic Environments |
| title_short | A Novel Online Path Planning Algorithm for Multi-Robots Based on the Secondary Immune Response in Dynamic Environments |
| title_sort | novel online path planning algorithm for multi robots based on the secondary immune response in dynamic environments |
| topic | multi-robots path planning immune network secondary immune response dynamic environment |
| url | https://www.mdpi.com/2079-9292/13/3/562 |
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