In view of the inaccurate positioning accuracy of the traditional Gmapping algorithm due to particle dissipation, the IPSO-Gmapping algorithm was proposed.By introducing similarity measurement parameters and new learning factors,the global development ability of particles in IPSO algorithm has been improved.And the phenomenon of falling into a "local optimal value"is avoided.Secondly,the optimized IPSO algorithm is applied to the traditional Gmapping algorithm,which makes particles move to the high likelihood region and improves the distribution of particles,which also makes the IPSO-Gmapping algorithm show excellent performance.The overall translation and rotation error is greatly reduced by using the common dataset and the actual scene for verification.Through experimental tests,it is proved that the proposed IPSO-Gmapping algorithm uses fewer particles and is superior to the traditional Gmapping algorithm in the accuracy of pose estimation and mapping accuracy.