Registration method of 3-D laser point cloud data of snow field

Laser point cloud registration is a crucial part of 3D reconstruction. The laser scanning of snow field is prone to noise and the lack of point cloud data leads to poor registration accuracy of point cloud. The optimized particle swarm optimization algorithm must be used to find the optimal spatial transformation matrix point cloud coarse registration method with point cloud distribution entropy as the optimal target, which provides good initial conditions for point cloud fine registration. Through simulation verification, it is proved that the point cloud entropy has faster calculation speed than the traditional mean squared difference evaluation method. The Particle Swarm Optimization based on Beetle Antennae Search Algorithm has the characteristics of strong global search ability and fast calculation speed. It shows better robustness under conditions of noise and missing data.