Path Planning And Track Tracking Of Slag Transporter Research And Simulation Of Control Algorithm

The slag carrier with automatic navigation capability can greatly improve production efficiency while reducing direct human participation in production activities.The slag carrier researched in this thesis can automatically navigate and avoid obstacles in the production workshop,safely return to the slag loading point and the slag unloading point,automatically plan a path without collision with obstacles,and the slag carrier can drive along the planned path.The path planning problem is to explore a path that does not collide with other obstacles such as slag carriers and production tools from the plane map in the working space of slag carriers.When the position of the obstacle is fixed,it is called the global path planning problem;When other unknown information appears near the slag transport vehicle,such as other slag transport vehicles and pedestrians,it is called the local path planning problem,and the length of the path distance is usually used as the evaluation criteria for different algorithms.The content of the research on the track tracking of the slag carrier is to make the controlled object make the error between the track of the slag carrier and the reference track zero within a certain time.For the above two core issues of automatic navigation of slag carrier,this thesis studies the relevant algorithms and proposes corresponding improvement methods based on the existing problems,and demonstrates the feasibility through simulation.In the first chapter of this thesis,the research status of mobile robots at home and abroad and the algorithms related to the path planning and track tracking of the slag carrier are introduced to clarify the research direction.In the second chapter,due to the shortcomings of traditional ant colony algorithm in the application of path planning,such as fast convergence and positive feedback,the planned path is often a suboptimal solution,the analysis found that genetic algorithm can effectively improve the randomness of initial path selection,and improved the classical ant colony algorithm by combining genetic algorithm and ant colony algorithm.Convert the workspace into occupied grid map,and analyze the advantages of the improved algorithm through the simulation results.In chapter 3,in the research of local path planning algorithm,the classical artificial potential field method establishes a virtual potential field in a dynamic environment,but it has the defect of relatively large repulsive force of obstacles near the target point.The relative distance between the slag carrier and the target point is taken as an adaptive term,and the improved repulsive force field function can effectively reduce the repulsive force of obstacles near the target point.Finally,in order to better track the planned path of the slag transport vehicle,the kinematics model of the slag transport vehicle is first established in Chapter 4,and then combined with the problem of system chattering that is easy to occur in the sliding mode control method,the double power approach law is adopted to weaken the chattering that occurs in the track tracking problem of the slag transport vehicle.The designed control law can make the position and attitude error of the slag transport vehicle close to zero in a short time under the Cartesian coordinate system,The path tracking is realized.The fifth chapter summarizes the deficiencies of the current research stage and the main directions of the next research.