Research On Control System Of Six-wheeled Distributed Driven Unmanned Vehicle

This project takes the initially designed six-wheel distributed drive unmanned vehicle as the research object,studies the key technologies of the six-wheel unmanned vehicle control system,and designs and implements a remote control system for the six-wheel unmanned vehicle with communication functions.The speed control and trajectory tracking control methods of the vehicle were studied,and the path planning technology in the obstacle avoidance and navigation method was improved.Finally,the autonomous navigation and obstacle avoidance simulation of the unmanned vehicle was completed based on ROS.The specific contents are as follows:(1)Analyze the key technologies of the unmanned vehicle control system,study the theoretical knowledge of unmanned vehicle motion control,obstacle avoidance algorithm and path planning algorithm,and summarize and extract the research direction and route of this topic,and introduce the research methods The ROS operating platform,a necessary tool for the human-vehicle control system,has laid a certain knowledge theory for subsequent research.(2)For the hardware design of the six-wheel unmanned vehicle,first select the main hardware of the system,design the required important circuits,write a motor control program in terms of control,and use the motor drive circuit to achieve independent driving of six motors.;Selected sensors and designed a data collection program,using cloud platform technology to realize wireless transmission of data;Finally,an unmanned vehicle hardware platform was built,and the remote control of the unmanned vehicle and real-time data were realized based on the Arduino development board.monitor.(3)Conducted research on the control method of unmanned vehicles,designed a fuzzy PID control algorithm,and used the particle swarm optimization algorithm to adjust and optimize the parameters of the fuzzy PID control algorithm.Through simulation,it was verified that the proposed algorithm has better overshoot than the traditional algorithm.It has the advantages of smaller size,shorter rise time and adjustment time,higher stability and more precise control.In terms of trajectory tracking,the LQR algorithm was designed,and based on the feedforward controller,the unmanned vehicle accurately tracked the expected trajectory.The unmanned vehicle model was established and simulated based on MATLAB/Simulink.(4)For the autonomous obstacle avoidance and navigation technology of unmanned vehicles,the A~* algorithm and DWA algorithm have been improved.The traditional A~*algorithm is optimized by improving the cost function.The optimized A~* algorithm has significantly reduced data in planning path length,planning time and path turning points,improving search efficiency.The traditional DWA algorithm is optimized by improving the evaluation function,making the planning path shorter,less planning time,and smoother.(5)In the ROS system,a simulation experiment platform was built,a SLAM twodimensional grid map was constructed,the AMCL algorithm was studied,and then AMCL positioning of unmanned vehicles was performed on the map,and the improved A~* algorithm and the improved DWA were used Combined with the algorithm,a simulation experiment was conducted on autonomous obstacle avoidance and navigation of an unmanned vehicle in a known grid map,which proved the feasibility of the improved algorithm.