Underground Face Drill Jumbos Path-planning Based on Improved Butterfly Optimization Algorithm

In this paper, a butterfly optimization algorithm is used for path planning of autonomous driving of underground trackless face drill jumbos. On account of the shortcomings of the traditional butterfly optimization algorithm whose parameters are complex and fixed in view of the more severe and complex environment of the actual underground mine path, a method based on adaptive adjustment of the power exponent parameters is proposed to improve it. The algorithm is applied to improve the search accuracy and iterative capability as opposed to the traditional butterfly optimization algorithm, which is verified by comparing the fitness function with the planning simulation of different simulation maps.