Path Planning of Robot in Coal Mine Using Genetic Membrane Algorithms

Abstract

Safety, intelligence and precision are the new trend of coal mining. To solve the influence of complex underground environment on the accuracy and reliability of robot path planning, a model of membrane computing system is constructed. Based on the efficient parallelism of the model, genetic membrane algorithm is designed to realize path planning for underground robots. The algorithm improves the efficiency of global search by applying the idea of solving the traveling salesman problem to the robot motion planning. Experiments proof the genetic membrane algorithm that can reduce the system error and has good convergence. Through stability analysis, it shows that the model and algorithm have theoretical feasibility and practical application value in path planning for the robot of coal mine.