A method was proposed for navigation mapping under complex indoor environment by using theimage sensor.Firstly,the pose of the camera was estimated based on VSLAM,and we got the 3D point cloud after the back-end optimization.Secondly,the ground point cloud was selected,and the ground plane equation was obtained based on the random sampling consensus algorithm.Finally,after projecting the point cloud of robots' passing area to the 2D grid map and updating the occupancy state of the grid by using Bayesian method,the indoor navigation mapping was implemented.Experimental results show that:1) The accuracy of indoor navigation map based on VSLAM can meet the navigation requirements,and 2) Different from the traditional mapping based on laser,the map based on VSLAM contains 3D environment structure information.In the path planning experiment,the planned path avoided the error of passing through the low objects and the suspended objects.