Experimental Research On The Path Planning Of The Walking System Of The Reed Shoot Harvester

Aiming at the demand for mechanization and intelligence of reed shoot harvesting in the Dongting Lake area,this paper carried out a pre-research on the intelligent obstacle avoidance path planning of the reed shoot harvester through theoretical calculation,Matlab simulation and experimental mobile platform verification.The system is based on the ROS(Robot Operating System)mobile platform operating system,using the extended Kalman filter SLAM(simultaneous localization and mapping)mapping and positioning scheme and the global and local fusion path planning algorithm.Finally,it is verified by simulation experiments and experimental tests.The effectiveness of the system.The main research content and conclusions of this paper are as follows:(1)Movement mode and sensor selection and model establishmentAccording to the growth environment and agronomy of the reed shoots,the movement mode of the harvesting platform was specifically selected.According to the advantages and disadvantages of different movement mechanisms,the movement mode of the crawler wheel differential drive was selected,and the kinematics model and The establishment of odometer error model.Lidar was selected as the main sensor,and the analysis and scanning model were established.(2)Travelling system mapping and positioning scheme designThe common map division methods were introduced and analyzed,and the most suitable grid map division scheme was selected.The positioning problem and classification are analyzed,and the overall plan of Kalman filtering positioning is discussed.Aiming at the non-linear characteristics of the whole system,the SLAM scheme of extended Kalman filter is researched and analyzed.And according to the plan,a framework for mapping and positioning nodes in the ROS operating system was designed,and the feasibility of the mapping and positioning framework was verified through preliminary simulation experiments.(3)Improvement and fusion of path search algorithmAn improved plan for the Astar global path algorithm was proposed on the grid map and simulated and verified by Matlab.At the same time,the DWA local path algorithm was optimized and verified by Matlab simulation.The two algorithms are further fused,and Matlab simulation is also used to verify the fusion algorithm.The simulation results show that the improved algorithm after fusion meets the expected path search requirements.(4)Experimental verification of distributed fusion walking systemPerform hardware selection,debug the experimental platform,and conduct experimental tests on the designed distributed fusion walking system based on the ROS system.Verify the SLAM,navigation,fusion path algorithm and mobile performance.