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Study of cable obstacle avoidance planning of a multi-robot collaborative towing system

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Abstract

In order to solve the problem of ignoring the cable and only planning the trajectory of the lifted object and the robot ends, a planning scheme of a multi-robot collaborative towing system aiming at the cable obstacle avoidance motion planning was proposed. The univariate polynomial equation group of the cable was obtained by constructing the cable sweep equation and defining the implicit equation of the obstacle. Then, the point-to-point decomposition trajectory was planned for the initial trajectory of the lifted object in the variable cable length workspace. And the differential manifold and manifold tangent space theories were used to plan the predicted trajectory of the lifted object. Based on the system dynamics characteristics, the tangent vector selection of the predicted trajectory was determined. Finally, the three-level planning strategy with the lifted object as the planning object, the end of robot as the planning intermediate, and the cable obstacle avoidance as the planning purpose was finally realized.

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Acknowledgments

The study was supported by the National Natural Science Foundation of China (Grant Nos. 51265021, 51965032) and Gansu Provincial Department of Education: Excellent Graduate Student “Innovation Star” Project (Grant No. 2022CXZX-571).

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Correspondence to Tao Li.

Additional information

Tao Li, male, was born in Pingliang City, Gansu Province, China, and is Master’s degree student. His research field is under-constrained multi-robot collaborative towing system for cable obstacle avoidance motion planning.

Zhigang Zhao, male, was born in Qingyang City, Gansu Province, China. He received his Ph.D. in Mechanical Engineering from Shanghai Jiaotong University. His research areas are special robots, multi-robot systems, and complex system identification and modeling.

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Li, T., Zhao, Z., Zhao, X. et al. Study of cable obstacle avoidance planning of a multi-robot collaborative towing system. J Mech Sci Technol 37, 3125–3139 (2023). https://doi.org/10.1007/s12206-023-0537-z

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  • DOI: https://doi.org/10.1007/s12206-023-0537-z

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