Research On Path Planning And Trajectory Tracking Control Method Of Tracked Vehicles

Tracked vehicles are often used in non-road environments such as hills,gravel,and wild ground because of their good passability and maneuverability.The safe and efficient operation has high requirements on the driver,in addition,it needs unmanned operation in the dangerous construction environment.The thesis combines the National Natural Science Foundation project "Electromechanical coupling dynamics and adaptive control of multi-crawler travelling gears"(No.51775225)to study the path planning and trajectory tracking of tracked vehicles to improve the vehicle’s intelligent level,thereby reducing dependence on operators.This article summarizes the research significance and the development status of smart tracked vehicles.It includes the discussion of common path planning algorithms and their advantages and disadvantages,the analysis of the research history and results of trajectory tracking technology,discusses the application and control advantages of model prediction control methods,and introduces common methods and application areas of positioning.Research on the path planning of tracked vehicles.Based on the grid method to build a grid map of the working environment of tracked vehicles,which is the basis for path planning and trajectory tracking.In order to find the shortest path,use A * algorithm for optimal path planning under six global maps,including maze conditions,random maps and irregular obstacle maps,etc.Use cubic B-spline curve to smooth the turning peaks of the obtained path.The experimental results confirm the rationality of the path planning algorithm and the effectiveness of using spline curve smooth sharp points.According to the speed and steering principle of the tracked vehicle in plane motion,the kinematic state space equation of the vehicle is established.Based on the model predictive control method,the tracked vehicle trajectory tracking controller is established.After introducing the overall control system solution,based on the vehicle model,the track speed on both sides is used as the control input to solve the predicted output of the system.After constraining the control amount,the model prediction controller is established by using S function.Several simulations with different preset speeds are performed under linear conditions,and the numerical simulation with different prediction time domains and control time domains are performed under continuous curves.The test validates the effectiveness of the controller,and the effects of speed and time domain parameters on the deviation are analyzed based on the results.Based on satellite positioning technology,trajectory tracking tests of the tracked vehicle prototype are carried out.After analyzing the positioning principle and common errors,the real-time kinematic technology is used to improve the positioning accuracy of the vehicle prototype.The hardware of the test platform includes a data acquisition system,a control execution system and a walking execution system,and the software part includes data processing and optimization control.The trajectory tracking experiments under different driving conditions are conducted,and the results show that the navigation tracking system can achieve good tracking performance.