| With the improvement of artificial intelligence,Auto mobile Vehicle has been widely used.SLAM technology is the basic technology of mobile robots and an important method for mobile robots to realize real-time self-positioning and environment mapping without prior information.Compared with other SLAM methods,laser SLAM has higher precision in map construction and can be directly used for positioning and navigation.In order to improve the intelligence of mobile robots in indoor activities,this paper improves the effect of positioning and navigation technology through the research of laser SLAM and path planning algorithm.ROS is the simulation platform for mobile robot experiments,and the motion characteristics of wheeled mobile robot are analyzed and the motion equation is established.The observation equation based on lidar was established,the environment raster map was established,and the environment raster was used in the path planning of mobile robot.The radar point cloud matching method provides necessary conditions for the positioning and navigation of the next moving robot.Research on SLAM method based on laser information.The probability model of SLAM is adopted to compare the advantages and disadvantages of extended Kalman filtering algorithm and particle filtering algorithm,and the Gmapping algorithm based on particle filtering is analyzed.An improved algorithm is proposed to improve particle allocation weight,working principle and working process,and the accuracy of SALM is improved.Carry out the research on the path navigation method of mobile robot.The optimal path planning is carried out by using the path navigation algorithm based on A* algorithm.The extension nodes are smoothed by introducing Dubins curve and Reeds-Shepp curve,and the overall planning route is smoothed by using B spline curve.The flow chart of the optimization algorithm is designed,and the practicability of the planning path is improved. |
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