Aiming at the large space indoor high-precision navigation application in complex environment, we propose an algorithm for integrated mapping and positioning based on workshop Measurement Positioning System (wMPS) and lidar. The wMPS carries out precise estimation on the position and orientation of the lidar, and integrates the point cloud data of the lidar to complete the mapping of the grid map. Therefore, the robot can recognize the information of the surrounding environment when navigating. Then considering that the wMPS measurement information is easy to be missing during navigating, we use particle filter algorithm to inversely calculate the position and orientation of the lidar according to the real-time point cloud data from lidar and the gird map. Finally, the results of particle filter are processed with the linear Kalman filter, and the algorithm simulation and experiment are conducted. The simulation and experimental results show that the integrated navigation system ensures the reliability of the map and the accuracy of the dynamic navigation, which greatly improves the overall performance of the navigation system.