Research on Indoor Positioning Method Based on LiDAR
In order to solve the problem of poor indoor GNSS positioning accuracy,an indoor high-precision positioning experiment is designed and implemented by using LiDAR technology.The experiment is carried out on the robot operating system platform,using Li-DAR to collect environmental information.The collected data are solved based on extended Kalman filter and graph optimization algo-rithm respectively to achieve indoor positioning,and the positioning accuracy of the two is compared.The experimental results show that the two indoor positioning methods can build high-precision environment map,and can effectively complete the indoor positioning task.The graph optimization SLAM has relatively high precision,and the environment map effect is better.
NETL
NSTL
万方数据
