Deviation Correction Path Planning Method of Full-Width Horizontal Axis Roadheader Based on Improved Particle Swarm Optimization Algorithm

Abstract

Aiming at the problem of optimal path planning for deviation correction of full-width horizontal axis roadheader in the confined roadway of the coal mine, a deviation correction path planning method of full-width horizontal axis roadheader based on improved particle swarm optimization (I-PSO) algorithm is proposed. First, according to the driving characteristics of roadheader and deviation correction strategy, the mathematical model of full-width horizontal axis roadheader is established, and the constraints based on pose analysis are determined. Then, taking the shortest total distance from the initial position to the terminal position of roadheader as the objective function of path planning, an optimization model of deviation correction path planning is established. Finally, the I-PSO algorithm is proposed to quickly and accurately solve the deviation correction path model, in order to plan a safe and shorter distance path of full-width horizontal axis roadheader. In the I-PSO algorithm, the fitness difference of particles is used to dynamically adjust the inertia weight parameters to optimize the exploration of the whole or part of activity space, and the learning factor is adjusted to speed up particle convergence and optimization of particles, and a random factor is introduced to update the position of particles to avoid local traps as much as possible. The performance test of the I-PSO algorithm shows that the I-PSO algorithm is superior to other algorithms. The EJM340/4-2 full-width horizontal axis roadheader is used as the simulation object to verify the effectiveness of the I-PSO algorithm in the deviation correction path planning of roadheader. The simulation results show that the I-PSO algorithm proposed can quickly and accurately plan a safe and shorter distance path than the WPSO algorithm and CPSO algorithm and has better convergence and stability. It has laid a good foundation for the intelligent navigation of full-width horizontal axis roadheader in coal mine.