Research On Path Planning Of Tracked Unmanned Platform In Dynamic Environment

The study of path planning technology is an important part of the research field of mobile robots,and it runs through the development history of robots.The ability of mobile robots to avoid obstacles in a dynamic environment is a difficult technique for local path planning.Ground mobile robots are mainly divided into wheeled robots and crawler robots.Wheeled robots are mainly used in the civilian field,with more extensive research,while the application fields of crawler robots are concentrated in the military,fire fighting,disaster relief and other fields,and relatively little research.Unmanned platform technology is mainly used to acquire surrounding environment information through a large number of sensors carried by itself,autonomously plan paths to make motion decisions,so that the unmanned platform can reach the target location safely and collision-free,and realize unmanned platform motion planning and navigation control.Crawler-type unmanned platforms have broad application prospects,and their movement methods and abilities are different from wheeled robots.For the requirements of global path planning and dynamic obstacle avoidance of crawler-type unmanned platforms in a dynamic environment,this paper studies the path planning technology of tracked unmanned platform under dynamic environment the main research contents are as follows:(1)The structure and working principle of the crawler-type unmanned platform are studied.The principle of differential speed is adopted for the crawler-type unmanned platform during steering,vehicle during steering,analyze the motion state of the vehicle during steering.The crawler-type unmanned platform is also established in order to facilitate the study of vehicle motion characteristics in the future.(2)An improved ant colony algorithm is proposed.In view of the characteristics of the crawler unmanned platform,the rough road surface,complex environment,and its own difficult turning,the path length,number of turns,and high smoothness are comprehensively considered,and the pheromone update method and heuristic function are modified in two directions..Constructed a non-uniform initial pheromone method and dynamically changed the volatilization coefficient,so that the algorithm converged quickly.Finally,a simulation model was built for experimental analysis.the traditional ant colony algorithm and the improved ant colony algorithm in this paper were simulated and compared.The comparison of simulation curves verifies the feasibility and effectiveness of the proposed method.(3)A dynamic window method with heuristic function changes is proposed.Aiming at the characteristics of the crawler-type unmanned platform which is large and difficult to turn,the curvature heuristic function is introduced to reduce the number of turns of the platform,and experimental verification is carried out.Finally,a combined path planning method based on improved ant colony algorithm and dynamic window method is proposed.(4)A simulation experiment platform was built.Introduce the Engineer unmanned crawler model in the Gazebo environment,build an experimental environment,use the lidar SLAM algorithm gmapping to generate a two-dimensional grid map,and use the combined path planning algorithm proposed above to plan the path from the starting point to the target point by replacing the algorithm plug-in in move?base,so as to complete the avoidance of static and dynamic obstacles in the map.