Research On Chassis Control System Design And Path Planning Of Tracked Detection Robo

With the development of science and technology,crawler mobile robots have become more and more widely used in various fields such as military,industry,and service industries.Especially in the field of military operations and detection,they have considerable potential application prospects.The main research points of crawler mobile robots cover motion control and autonomous navigation control.This paper studies the design of its control system and the optimal path planning problem when part of the environment is unknown.The specific research content is as follows:(1)Carry out the kinematics model of the crawler mobile robot and analyze its movement performance.Combining the functions that the robot needs to achieve,select the robot’s power devices,control devices,and sensors.So as to lay the foundation for the design of the followup control system and the realization of the algorithm.(2)Research the problems of large overshoot and unsatisfactory real-time performance in the crawler robot control system and mainstream PID control algorithm.With the STM32F427 chip as the core,the control system of the crawler mobile robot chassis is established.The embedded real-time operating system Free RTOS divides the entire control system into 5modules: host computer communication module,gyroscope data settlement and upload module,remote control module,status monitoring module and motion control module.Design the software and communication protocol for each module respectively.In the motion control module,in view of the problems of large overshoot and time lag in traditional PID control,gray prediction algorithm is used to improve it,which further reduces the overshoot of the system and enhances the stability of the system.In addition,the speed curve during the operation of the robot is printed out through actual tests.Adjust the parameters of the control algorithm according to the waveform and verify the effect of the improved algorithm.(3)In view of the large amount of calculation in the global path planning of the A*algorithm,the tortuous trajectory and the problem of being too close to obstacles,an improved algorithm combining map preprocessing and trajectory secondary optimization is proposed.This effectively improves the search efficiency of the original algorithm while making the generated path distance shorter and smoother.In the local path planning,the DWA algorithm is combined with the improved A* algorithm.The cost function is improved by the sub-target point orientation evaluation factor,which improves the validity and smoothness of the path,and realizes the local obstacle avoidance based on the improved A* algorithm.(4)The algorithm proposed in this paper is verified by actual test.Established grid maps of two environments using lidar,and verified the improved A* algorithm and DWA algorithm using the ROS navigation system framework.The crawler robot’s global planning and local obstacle avoidance capabilities are tested when the map information is known and partly unknown.The test results show that the improved algorithm is effective and practical.