Multitarget Search of Swarm Robots in Unknown Complex Environments
When searching for multiple targets in an unknown complex environment, swarm robots should firstly form a number of subswarms autonomously through a task division model and then each subswarm searches for a target in parallel. Based on the probability response principle and multitarget division stra...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/8643120 |
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| _version_ | 1832553502051663872 |
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| author | You Zhou Anhua Chen Hongqiang Zhang Xin Zhang Shaowu Zhou |
| author_facet | You Zhou Anhua Chen Hongqiang Zhang Xin Zhang Shaowu Zhou |
| author_sort | You Zhou |
| collection | DOAJ |
| description | When searching for multiple targets in an unknown complex environment, swarm robots should firstly form a number of subswarms autonomously through a task division model and then each subswarm searches for a target in parallel. Based on the probability response principle and multitarget division strategy, a closed-loop regulation strategy is proposed, which includes target type of member, target response intensity evaluation, and distance to the corresponding individuals. Besides, it is necessary to make robots avoid other robots and convex obstacles with various shapes in the unknown complex environment. By decomposing the multitarget search behavior of swarm robots, a simplified virtual-force model (SVF-Model) is developed for individual robots, and a control method is designed for swarm robots searching for multiple targets (SRSMT-SVF). The simulation results indicate that the proposed method keeps the robot with a good performance of collision avoidance, effectively reducing the collision conflicts among the robots, environment, and individuals. |
| format | Article |
| id | doaj-art-d31fdb18c94a4e4db5fc1de3044805ea |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-d31fdb18c94a4e4db5fc1de3044805ea2025-02-03T05:53:56ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/86431208643120Multitarget Search of Swarm Robots in Unknown Complex EnvironmentsYou Zhou0Anhua Chen1Hongqiang Zhang2Xin Zhang3Shaowu Zhou4College of Mechanical and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, Hunan Province, ChinaCollege of Mechanical and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, Hunan Province, ChinaSchool of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, Hunan Province, ChinaSchool of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, Hunan Province, ChinaSchool of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, Hunan Province, ChinaWhen searching for multiple targets in an unknown complex environment, swarm robots should firstly form a number of subswarms autonomously through a task division model and then each subswarm searches for a target in parallel. Based on the probability response principle and multitarget division strategy, a closed-loop regulation strategy is proposed, which includes target type of member, target response intensity evaluation, and distance to the corresponding individuals. Besides, it is necessary to make robots avoid other robots and convex obstacles with various shapes in the unknown complex environment. By decomposing the multitarget search behavior of swarm robots, a simplified virtual-force model (SVF-Model) is developed for individual robots, and a control method is designed for swarm robots searching for multiple targets (SRSMT-SVF). The simulation results indicate that the proposed method keeps the robot with a good performance of collision avoidance, effectively reducing the collision conflicts among the robots, environment, and individuals.http://dx.doi.org/10.1155/2020/8643120 |
| spellingShingle | You Zhou Anhua Chen Hongqiang Zhang Xin Zhang Shaowu Zhou Multitarget Search of Swarm Robots in Unknown Complex Environments Complexity |
| title | Multitarget Search of Swarm Robots in Unknown Complex Environments |
| title_full | Multitarget Search of Swarm Robots in Unknown Complex Environments |
| title_fullStr | Multitarget Search of Swarm Robots in Unknown Complex Environments |
| title_full_unstemmed | Multitarget Search of Swarm Robots in Unknown Complex Environments |
| title_short | Multitarget Search of Swarm Robots in Unknown Complex Environments |
| title_sort | multitarget search of swarm robots in unknown complex environments |
| url | http://dx.doi.org/10.1155/2020/8643120 |
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