Global Path Planning And Trajectory Tracking Of Unmanned Wheeled Vehicles On Terrains

Off-road vehicle autonomous driving technology has a wide range of uses in military,agricultural,firefighting and other fields.In this paper,we study the global path planning and trajectory tracking algorithms for unmanned wheeled vehicles on unstructured roads in off-road environments.At present,there are many global path planning algorithms in grid maps on unstructured roads,while general grid maps do not consider the specific elevation or ground type difference of each grid.On the other side,unstructured roads are generally considered as flat and open roads.The unmanned offroad is always a bumpy road with undulating terrain,and meanwhile,the landform is complex and the types of features are diverse.Relying on the National Defense Science and Technology Innovation Special Zone project,this article carries out research on path planning and trajectory tracking methods for unmanned off-road vehicles on typical off-road pavements.Firstly,I will select the experimental area around Changchun,and the environment was modeled through land monitoring analysis and DEM information.Then,the global and local path planning algorithms were used to simulate in order to obtain the discrete track set of off-road vehicle references.Finally,a driver model was built for trajectory tracking based on the preview control,and the effectiveness of the local path planning algorithm was verified.The main contents of this article include:(1)terrains environment modellingThe modeling process including BP neural network for land supervision classification,and DEM elevation data to calculate slope and aspect information.The classification result is modeled by the grid method to obtain an off-road grid map that the vehicle can recognize.(2)Simulation of path planning algorithmIn the off-road grid map,the improved A * algorithm and the improved ant colony algorithm are used for global path planning.Then we will compare the simulation results between the two algorithms.Among them,the improved A * algorithm has a shorter path travel time,so the subsequent selection is used for local path planning,and the local path resolution is improved to refine the grid map information."Rolling window method and HCAA * algorithm" is used to realize the local path planning of the offroad map.It can obtain the trajectory curve that the vehicle can pass,and then we will calculate the vertical speed on the trajectory curve based on the ground attribute information.Finally we will obtain the trajectory point including the coordinates and vehicle speed.(3)Trajectory tracking control algorithmThe vehicle’s lateral and longitudinal dynamic models are established.The lateral control algorithm based on the preview control theory and the PID-based longitudinal control algorithm are established respectively.The feedback control adjustment based on the heading angle error.The effectiveness of the trajectory tracking control algorithm is verified by the fixed curvature condition and the double-shifted condition.(4)Simulation verification of local path planning for off-road mapBased on the above theoretical basis,the off-road pavement under the Carsim environment is constructed by the off-road grid map.I will build a trajectory tracking control model through MATLAB / Simulink,and the joint simulation of Carsim and Simulink is performed based on the local trajectory points obtained by the HCAA * algorithm.The results show that the trajectory tracking algorithm can achieve real-time control of vehicles passing along a predetermined trajectory,and it also has better control effect.At the same time,the trajectory curve obtained by local planning can meet the vehicle’s constraint requirements.