Measurement And Construction Of Vehicle Front Pavement Elevation Based On Multi-sensor Information Fusion

In the process of vehicle driving,the main incentive of the vehicle comes from the road surface.Road roughness has an important impact on the ride comfort and handling stability of the vehicle.Suspension is the connecting part between bridge and body.Its parameters directly affect the response of body to road excitation.Therefore,how to accurately obtain the elevation information of the road ahead of the vehicle and then control the suspension is the key factor to improve the ride comfort of the vehicle.In this paper,the method of measuring and constructing the elevation information of the road surface in front of the vehicle is studied based on the subject of " Research on Road Condition Recognition Technology for Active Suspension Development of All-terrain Crane" of the National Key Laboratory of Intelligent Manufacturing of High-end Construction Machinery.In this paper,the real-time position and attitude information fusion of vehicle is completed by using encoder,inertial navigation system(INS)and global positioning system(GPS)through extended Kalman filter.The point cloud information of road surface is collected by lidar,and then the road elevation information in front of vehicle is measured by combining with real-time position and attitude of vehicle.The recognition is completed by Kriging interpolation algorithm.Accurate construction of road surface in front of other vehicles.Firstly,the research status of road spectrum recognition,road surface recognition,pose perception and three-dimensional scene reconstruction at home and abroad are introduced.Then,the sensor selection is completed,and the installation scheme of the sensor is worked out according to the actual working conditions and the test bench is built.The external parameter calibration scheme of lidar is proposed to complete the calibration of the installation position and angle of lidar,and the coordinate transformation relationship between lidar and INS is accurately obtained by joint calibration.Based on Robot Operating System(ROS),the software platform of the system is designed and built.The coordinate system needed by the system is introduced,and the URDF three-dimensional mathematical model is built.Then the sensor nodes and control nodes are built,and the topic is established to complete the communication between the nodes.The kinematics model of the vehicle is established to transform the encoder data into the real-time pose transformation of the car body coordinate system.The method of obtaining the real-time pose of the car body coordinate system by INS and GPS is introduced.Based on Extended Kalman Filter(EKF),the model of single sensor position and attitude measurement system and the fusion of multi-sensor position and attitude measurement information are completed,and the real-time accurate position information of car body coordinate system is obtained.The dynamic model of the testbed is built to obtain the position and posture of the car body coordinate system by simulation,and the algorithm of position and posture information fusion is validated by building the road surface to complete the experiment.Through the collection of point cloud data by lidar,the integration of the data collected by lidar and the real-time position and posture of the vehicle body completes the establishment of three-dimensional point cloud of the road ahead of the vehicle.The extraction of point cloud of the driving road ahead is completed through the preprocessing of point cloud,and then the construction of the road ahead of the vehicle is completed based on Kriging algorithm.The experimental results are analyzed,and the algorithm is revised by comparing with the actual road surface,and the causes of the errors are analyzed,so as to facilitate the further improvement of the measurement system of the road surface elevation information proposed in this paper.In this paper,based on multi-sensor information fusion,the measurement and construction system of road elevation information in front of vehicles is built,including the installation and calibration of sensors,the design and construction of system software platform,the realization of multi-sensor position and attitude information fusion,and the construction of road surface through the elevation point cloud data of road surface,and the verification of the system is completed by building a test bench.