Xiangtang Zhao
(, ), Zhigang Zhao
(, ), Cheng Su
(, ), Jiadong Meng
(, ), Hutang Sang
(, )
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The optimal obstacle avoidance trajectory of the multi-robot suspension system can be accurately determined by using the collaborative optimization method for force and position to plan the towing robot and the cable. Finally, the correctness of the obstacle avoidance planning method is verified by simulations. By taking a special scenario, the remarkable findings reveal that the SDBO algorithm outperforms the dung beetle optimization algorithm by reducing the length of the planned trajectory of the suspended object by 14.51% and the height by 79.88%, and reducing the minimum fitness by 95.84% and the average fitness by 94.77%. The results can help the multi-robot suspension system to perform various towing tasks safely and stably, and extend the related planning and control theory.\n</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":7109,"journal":{"name":"Acta Mechanica Sinica","volume":"41 12","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficient obstacle avoidance planning for multi-robot suspension system based on a collaborative optimization for force and position\",\"authors\":\"Xiangtang Zhao \\n (, ), Zhigang Zhao \\n (, ), Cheng Su \\n (, ), Jiadong Meng \\n (, ), Hutang Sang \\n (, )\",\"doi\":\"10.1007/s10409-024-24456-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>To avoid collisions between a suspended object, cables, towing robots, and obstacles in the environment in a multi-robot suspension system, obstacle avoidance planning was studied based on a collaborative optimization method for force and position. Based on the analysis of the kinematics and dynamics of the system, the inverse kinematics and inverse dynamics of the system are solved using the least variance method. The obstacle avoidance planning is performed in the solved collision-free feasible space using the stable dung beetle optimization (SDBO) algorithm, which ensures that the suspended object can move stably to the target point in the workspace. The optimal obstacle avoidance trajectory of the multi-robot suspension system can be accurately determined by using the collaborative optimization method for force and position to plan the towing robot and the cable. Finally, the correctness of the obstacle avoidance planning method is verified by simulations. By taking a special scenario, the remarkable findings reveal that the SDBO algorithm outperforms the dung beetle optimization algorithm by reducing the length of the planned trajectory of the suspended object by 14.51% and the height by 79.88%, and reducing the minimum fitness by 95.84% and the average fitness by 94.77%. 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Efficient obstacle avoidance planning for multi-robot suspension system based on a collaborative optimization for force and position
To avoid collisions between a suspended object, cables, towing robots, and obstacles in the environment in a multi-robot suspension system, obstacle avoidance planning was studied based on a collaborative optimization method for force and position. Based on the analysis of the kinematics and dynamics of the system, the inverse kinematics and inverse dynamics of the system are solved using the least variance method. The obstacle avoidance planning is performed in the solved collision-free feasible space using the stable dung beetle optimization (SDBO) algorithm, which ensures that the suspended object can move stably to the target point in the workspace. The optimal obstacle avoidance trajectory of the multi-robot suspension system can be accurately determined by using the collaborative optimization method for force and position to plan the towing robot and the cable. Finally, the correctness of the obstacle avoidance planning method is verified by simulations. By taking a special scenario, the remarkable findings reveal that the SDBO algorithm outperforms the dung beetle optimization algorithm by reducing the length of the planned trajectory of the suspended object by 14.51% and the height by 79.88%, and reducing the minimum fitness by 95.84% and the average fitness by 94.77%. The results can help the multi-robot suspension system to perform various towing tasks safely and stably, and extend the related planning and control theory.
期刊介绍：
Acta Mechanica Sinica, sponsored by the Chinese Society of Theoretical and Applied Mechanics, promotes scientific exchanges and collaboration among Chinese scientists in China and abroad. It features high quality, original papers in all aspects of mechanics and mechanical sciences.
Not only does the journal explore the classical subdivisions of theoretical and applied mechanics such as solid and fluid mechanics, it also explores recently emerging areas such as biomechanics and nanomechanics. In addition, the journal investigates analytical, computational, and experimental progresses in all areas of mechanics. Lastly, it encourages research in interdisciplinary subjects, serving as a bridge between mechanics and other branches of engineering and the sciences.
In addition to research papers, Acta Mechanica Sinica publishes reviews, notes, experimental techniques, scientific events, and other special topics of interest.
Related subjects » Classical Continuum Physics - Computational Intelligence and Complexity - Mechanics
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