Method of cutting trajectory planning of roadheader based on hybrid IWO-PSO algorithm

In order to solve the problems of low accuracy and large loss of heading equipment in cutting trajectory planning method of roadheader, a cutting trajectory planning method of roadheader based on hybrid IWO (invasive weed optimization)-PSO (particle swarm optimization) algorithm is proposed. The cutting section environments are divided into three types, namely single gangue, double gangue and multi-gangue, and the corresponding sections are rasterized and the grid map is established. The irregular gangue is expanded by using binary expansion method. The hybrid IWO-PSO algorithm is used for trajectory planning in the three types of section environments. The hybrid IWO-PSO algorithm is based on the seed diffusion method in IWO algorithm, which diffuses the initial population and allows all individuals to reproduce freely before competitive exclusion, thus effectively ensuring the diversity of optimization space. The position iterative update method in PSO algorithm is also used to iteratively update the reproduced seed positions, and the particle positions are adjusted in time by using group experience and individual experience to improve the optimization depth and speed of the algorithm effectively. The simulation results show that the length of cutting trajectory, the number of secondary excavation grids and the cutting energy consumption of the roadheader based on the hybrid IWO-PSO algorithm are smaller than those of the standard PSO algorithm, and the capability to avoid the obstacle and gangue is better than that of the standard PSO algorithm. The section cutting test is carried out by EBZ135 roadheader, and the results show that the maximum errors of the left side, right side and both sides of the roadway section forming are 30, 20 and 50 mm respectively, and the relative error is within 2%, 1.4% and 1.7% respectively, which can meet the requirements of effective obstacle avoidance and forming under different roadway section environments.