Research On Path Planning And Tracking Control Of AGV Dropping Vehicle

The textile industry is developing rapidly towards automation and intelligence.Intelligent production lines have become the current mainstream form.Traditional textile workshops still rely on manual forklifts to carry the warp beams.This is not only time-consuming and laborintensive,but also due to the large volume and weight of the warp beams.It is easy to roll off,and the full axle state is generally about 400 kg,which seriously threatens the personal safety of workers.Therefore,this thesis designs an Automated Guided Vehicle to replace the manual transport of the warp beam,which not only greatly reduces labor costs,but also greatly reduces labor costs.Efficient and convenient transportation methods have improved the production efficiency of enterprises.Combined with the requirements of a certain enterprise,in-depth research on path planning and path tracking in the robot movement process is carried out to realize the precise control of navigation and movement in the autonomous handling process.The thesis is mainly divided into the following parts:(1)Constructed the mechanical structure model of the AGV drop car,established that the AGV studied in this thesis is a dual-steering wheel drive diagonally distributed structure,and established the kinematics model of the AGV drop car on this basis,laying a theoretical foundation for the following article.(2)The AGV global path planning strategy based on improved genetic algorithm is designed.The strategy first uses prior knowledge to optimize the initial population;further redesigns the crossover and mutation formulas to reduce the possibility of falling into the local optimum;then introduces the path smoothness and the shortest path as the criterion in the fitness function;and finally Different environments are selected for simulation and comparison experiments to verify the effectiveness of the algorithm proposed in this thesis.(3)Based on the kinematics model of the AGV drop car,the PSO-PID path tracking control algorithm of the AGV drop car is designed.The improved inertia weight cosine adjustment particle swarm algorithm is used to optimize the PID controller parameters,and the linear and curvilinear paths are selected for path tracking simulation comparison experiments.The results show that the PSO-PID control designed in this thesis is better than the traditional PID control in terms of control accuracy,response time,and stability.(4)Designed the human-computer interaction interface for the path planning of the AGV drop vehicle.Using MATLAB 2018 b and Visual Studio as the development platform,the manmachine interactive interface for the path planning of the AGV drop car was designed,and the software performance was tested.The test results showed that the software can complete the path planning task.Finally,a test experiment on the path tracking control of the AGV drop vehicle was completed in the laboratory.The experimental results show that the PSO-PID controller designed in this thesis can stably perform path tracking control on the trolley.