Operation Path Planning Of Unmanned Construction Machinery Based On Potential Field Ant Colony Algorithm

Under the background of industry 4.0,the utilization rate of construction machinery is increasing rapidly.With the progress of manufacturing capacity and the requirements of modern project construction clustering and safety,driverless technology has become a major development direction of construction machinery.Path planning,as one of the key technologies in the field of unmanned driving,has been quietly rising at home and abroad,but the traditional path planning methods do not fit in the application of unmanned construction machinery.Taking unmanned construction machinery as the research object,this paper studies the path planning problem of construction machinery based on multi intelligence algorithm fusionFirstly,this paper analyzes the working environment characteristics of unmanned construction machinery in detail,and determines the environment map modeling based on grid map to accurately express obstacles and feasible areas.In order to provide accurate and effective environmental information for the path planning of unmanned construction machinery,the possible unfilled grid and trap grid are expanded and filled respectively.Secondly,the artificial potential field method is applied to the local path planning of unmanned construction machinery in complex environment.Aiming at the problems of inaccessibility and tortuous path of the artificial potential field algorithm,the improvement methods of repulsion field function and forward direction angle setting are proposed respectively,and the improvement effect of the algorithm is verified by matlab simulationThen,the principle and mathematical model of ant colony algorithm are introduced,and the defects of its application in global path planning of complex environment map are analyzed.The algorithm is improved by introducing pseudo-random proportion transfer and pheromone release rules;Combined with the potential field force to form the comprehensive heuristic information,the speed of the early iteration and convergence is improved;The weight coefficient of potential field force is introduced.In the early stage,the potential field force dominates the algorithm search to improve the iterative efficiency.In the later stage,the ant colony algorithm is inspired by information to improve the local optimization problem;Through the MATLAB simulation experiment,it is verified that it has good convergence speed and accuracy.Finally,the system shows the developed host computer interface.Through the detailed introduction of project management,construction machinery group management and other different modules,it provides a unified platform for algorithm use and project monitoring management,and lays a good foundation for intelligent construction machinery group cooperative construction.