Data-driven optimization method for automatic shoveling trajectory of loaders

Tao Zhou; Bingsen Chen; Yanhui Chen; Cheng Tan

doi:10.1117/12.2688748

18 July 2023 Data-driven optimization method for automatic shoveling trajectory of loaders

Tao Zhou, Bingsen Chen, Yanhui Chen, Cheng Tan

Proceedings Volume 12744, Second International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2023); 1274412 (2023) https://doi.org/10.1117/12.2688748
Event: Second International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2023), 2023, Nanjing, China

Abstract

A trajectory planning method for automatic shoveling is proposed to achieve energy saving and efficiency improvement when the loader performs automatic shoveling operations. Firstly, the planning of the shoveling trajectory is based on the matching shoveling method. Then the automatic shovel operation test was conducted to obtain relevant operational performance parameters according to different shovel depths. A shovel trajectory optimization method is proposed based on modified parabolic interpolation of test data. The test results of shovel trajectory planning showed that the error was reduced from 9.1% to 0.6% after optimization. And according to the optimized trajectory for automatic shoveling compared with manually controlled shoveling, the operating time increased by 2.29%, the shoveling weight decreased by 3.2%, and the unit shoveling fuel consumption decreased by 11.29%. The test results and calculation process show that the method can quickly find the optimized shoveling trajectory, effectively reducing the operation's energy consumption.

Citation Download Citation

Tao Zhou, Bingsen Chen, Yanhui Chen, and Cheng Tan "Data-driven optimization method for automatic shoveling trajectory of loaders", Proc. SPIE 12744, Second International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2023), 1274412 (18 July 2023); https://doi.org/10.1117/12.2688748

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