Positioning And Tracking Control In Navigation Of Tracked Transfer Vehicles In Hilly Mountainous Areas

Hilly mountainous areas with complex terrain and poor road conditions,some agricultural mobile transfer equipment is difficult to access,resulting in difficulties in the handling of agricultural products and agricultural supplies,there is an urgent need for an automated mobile transfer equipment with high navigation and positioning accuracy and strong independent control capability.Therefore,to address the problems of poor satellite positioning accuracy and satellite positioning signal loss due to the curved and circuitous routes and tree shading in hilly mountainous areas,we build an experimental platform for crawler-type transfer vehicles to achieve autonomous operation in hilly mountainous areas,study the fusion positioning algorithm based on GNSS,INS and LIDAR and the autonomous path tracking control technology of crawler-type transfer vehicles,and conduct experimental verification of the proposed algorithm based on the experimental platform of crawler-type transfer vehicles.The main research contents include:(1)Construction of the navigation system of the tracked transfer vehicle.For the natural environment features such as dense vegetation and winding roads in hilly mountainous areas,a crawler-based test platform was built to determine the overall architecture of the hardware and software of the crawler-type transfer vehicle.The GNSS navigation system based on carrier phase difference(RTK)technology,INS inertial reference system and LIDAR were selected to realize navigation and positioning,and the hardware sensors were analyzed for errors and selected.(2)INS error modeling.Establish the equations for attitude solution,velocity solution and position solution of INS.On this basis,the error theory model of inertial sensors and the INS error equation are constructed to lay the foundation for the subsequent combined navigation information fusion model.(3)Construction of GNSS/INS combined navigation system.The system equations of GNSS/INS are designed according to the error model of INS.Based on this,the adaptive Kalman filter based on the Marxian distance is designed for information fusion to resist anomalous observation and model errors,in view of the difficulty of the combined navigation system to obtain accurate system state model parameters in hilly mountainous areas and the phenomenon of measurement anomalies in hilly mountainous areas.Compared with the extended Kalman filter,the adaptive Kalman filter based on the Marxian distance reduces the position error by 10.3%,13.1% and 9.7%,and the velocity error by 11.9%,11.4% and 8.6% in the east,north and sky directions.The experimental results show that the adaptive filter based on the Marxian distance designed in this paper has excellent results in data fusion.(4)The study of LIDAR/INS fusion positioning algorithm for crawler-type transfer vehicle in the case of GNSS signal loss lock.For the phenomenon of hilly mountainous areas with lots of vegetation and easy GNSS signal loss lock,LIDAR uses LOAM algorithm for positioning,then EKF is used to fuse LIDAR positioning data with INS positioning data,and finally the fusion algorithm is tested and the obtained results are compared with the true value positioning data.The average northward positioning error of the combined LIDAR/INS navigation is 0.15 m,and the average eastward positioning error is 0.13 m.The results show that the positioning accuracy of the combined LIDAR/INS navigation is not sufficient in the case of GNSS signal losing lock for a long time,but it can meet the positioning accuracy of autonomous vehicles in a short time.(5)Optimization design of path tracking controller.Under the premise of known path planning and positioning information,the kinematic model and trajectory tracking error model of the crawler-type transfer vehicle are studied in depth,and the trajectory tracking algorithm,i.e.,the sliding mode trajectory tracking control algorithm,is firstly designed for the hilly mountainous environment with multiple disturbance characteristics.The stability of the whole closed-loop control system is analyzed,and the whole closedloop control system of the crawler transporter is proved to be asymptotically stable.Then a three-loop PID algorithm is designed for the path tracking control.Next,the whole control system is simulated and verified in the working conditions of uniform linear motion and uniform circular motion.Finally,the trajectory tracking control test is conducted under different working conditions based on two kinds of combined navigation as the positioning method.The test and simulation results show that the control algorithm designed in this paper can achieve excellent accuracy in trajectory tracking and has high robustness to external disturbances.