Abstract: In order to solve the problem that the ICP ( Iterative Closest Point) algorithm has strict requirements on the initial point cloud position and is easy to be trapped in local optimum，a new registration method is proposed． Firstly，based on the idea of complementary advantages，the artificial glowworm algorithm and particle swarm algorithm are combined to propose an AAGPSO ( Adaptive Artificial Glowworm-Particle Swarm Optimization) ，accelerating the convergence speed of the algorithm and improving the accuracy of the solution．Secondly，for a different initial location of the point cloud，the improved AAGPSO algorithm is introduced into the ICP registration algorithm making ICP algorithm optimized，and solving the local optimum problem of the ICP
algorithm． The improved algorithm accelerates the overall registration efficiency． Finally，experimental data are used to compare the original ICP registration method with the improved registration method，and the error analysis is carried out． The AAGPSO algorithm improves the registration accuracy，accelerates the algorithm convergence speed．

Key words: artificial glowworm-particle swarm optimization algorithm ( AAGPSO) , point cloud registration, iterative closest point ( ICP) algorithm