Excavation trajectory planning for unmanned mining electric shovel using B-spline curves and point-by-point incremental strategy under uncertainty

Abstract

The intelligence of electric shovels plays a critical role in improving excavation efficiency and safety. A key challenge in intelligent excavation is generating an optimal excavation trajectory while considering material uncertainty. Therefore, an Unmanned mining Electric Shovel Trajectory Planning method based on the Point-by-point Incremental B-spline Curve under Uncertainty (UESTP-PIBCU) is proposed in this paper. The method establishes the dynamic model of the electric shovel working mechanism and the excavation resistance model, analyzes excavation resistance uncertainty parameters using interval possibility theory. Then, a multi-objective trajectory planning model considering excavation resistance uncertainty is established, and the optimal excavation trajectory is obtained through optimization. Experimental results demonstrate that UESTP-PIBCU outperforms commonly used methods in excavation efficiency and dipper fill ratio, and operational efficiency is effectively improved. Future research will explore the impact of multi-source uncertainties on excavation trajectories, to enhance the reliability and robustness of the intelligent electric shovel system.