| The autonomous navigation technology of the ground unmanned platform has been widely used in many fields,especially in some high-pressure,high-temperature,radioactive hazardous operation scenarios,which can replace human to complete the task.In this scenario,the unmanned platform needs to be able to complete the navigation work by sensing the surrounding environment in the unknown environment.At present,there is still room for improvement in many aspects of the technology.In this paper,the surface unmanned platform for outdoor unstructured scenes is taken as the object,and the map building method based on multi line lidar,the navigation path planning method in dynamic environment and the path tracking and control method are mainly studied.First of all,in the part of simultaneous positioning and mapping based on lidar,Le GO-LOAM algorithm is used,which improves the commonly used LOAM algorithm.Through the processing of point cloud segmentation and clustering,point cloud downsampling,feature point screening and spatial allocation,the iterative calculation of the matching process in the laser odometer is reduced,so that the mapping algorithm can adapt to more complex environment.More accurate pose estimation results are obtained by matching point cloud with map feature points.According to the result,the point cloud is corrected and the map of point cloud is constructed and updated.Secondly,on the premise of the existing navigation map,the path of the unmanned platform to the target point is planned.The advantages and disadvantages of A* algorithm and Dijsktra algorithm are compared by theory and simulation,and A* algorithm is selected as the global path planning algorithm.For the local path planning problem in dynamic environment,this paper improves the traditional artificial potential field method,and analyzes the local minimum points,dynamic obstacle constraints and so on.Finally,the specific process of hybrid path planning algorithm is introduced.In addition,a model predictive controller with feedforward structure is designed based on the kinematic model of the unmanned mobile platform to track the planned path.The controller takes into account the control quantity and control increment constraints of the unmanned platform.Through theoretical analysis,the stability of the system under the control strategy is proved.The effectiveness of the algorithm is verified by simulation analysis under different speed and different path conditions.The bottom control board is designed to control the longitudinal velocity and yaw rate.Finally,the hardware system of the unmanned platform is built,and the program is written in ROS environment.The real-time construction of lidar point cloud map is realized in indoor environment.Due to the limitation of experimental conditions,the simulation of autonomous navigation system is carried out by using Gazebo simulation software,and the experimental results are analyzed. |
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