Path Tracking Control for Autonomous Driving of Unmanned Mining Shovel

doi:10.3901/JME.2025.20.318

Abstract

Abstract: The safety and high efficiency of long-distance movement as well as the accurate and timely digging position adjustment of the mining shovel serve as the base for productive continuous open-pit mining operation. Considering the disadvantages of the driving activities by operators such as the limited view range, the awareness delay and fatigue driving, a Pre-sighting Fuzzy Control algorithm was established in this paper to achieve the autonomous path tracking of mining shovel diminishing the human effects. Firstly, both the long and short distance driving characters of mining shovels were analyzed, based on which the self-driving strategy was established. Then, the dynamic model of the heavy crawler equipped by mining shovels was built and the Pre-sighting Fuzzy Control algorithm was constructed for the autonomous path tracking task. One step further, simulations with different initial error status based on virtual prototype of a scaled unmanned mining shovel was accomplished to validate the accuracy and the adaptiveness of the algorithm. At last, the physical prototype was built and field tests were applied for the path tracking performance in different conditions such as curve tracking, obstacle avoidance forward moving and ‘V’ type lateral movement. Results showed the high accuracy and stability of the algorithm that the heading angle error could be controlled into about ±2 ° and the track error within ±10 cm, which proves the effectiveness for autonomous path tracking for unmanned mining shovels.

Key words: mining shovel, autonomous driving, pre-sighting fuzzy control, path tracking, scale model test

CLC Number:

TD422

TAN Xiaodan, LI Jing, FANG Yi, XU Tianshuang, WANG Yongpeng, HUANG Qingxue. Path Tracking Control for Autonomous Driving of Unmanned Mining Shovel[J]. Journal of Mechanical Engineering, 2025, 61(20): 318-327.

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