Open AccessMulti-objective Excavation Trajectory Optimization for Intelligent Electric Shovel Based on ROS
Author(s) -
Zifei Fan,
Tianci Zhang,
Jianqiang Qiao,
Guang Li,
Yonggang Zhao,
Xin Wang,
Wei Sun,
Xueguan Song
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/717/1/012015
Subject(s) - shovel , excavation , trajectory , computer science , minification , volume (thermodynamics) , mathematical optimization , automotive engineering , engineering , mechanical engineering , mathematics , physics , geotechnical engineering , quantum mechanics , astronomy , programming language
Electric shovel is a large-scale excavation equipment, which often suffer from discontinuous and inefficient excavation due to complicated mine condition. To address these challenges, a multi-objective optimization strategy for electric shovel is proposed to achieve an efficient, stable and intelligent operation. Firstly, the dynamical model of the electric shovel system is established based on Lagrange method. Then, the minimum energy consumption per volume and minimum relief angle difference are regarded as the optimization formulation considering multiple system constraints. Finally, the strategy is applied to the ROS-based intelligent prototype of shovel to verify the effectiveness. The results show that the multi-objective optimization strategy of the excavation trajectory has great guiding significance for the design of the intelligent electric shovel.