Abstract

Aiming at the problem of point cloud registration, a registration method based on dynamic differential evolution algorithm (DDE) is proposed. The voxel grid method is used to uniformly sample the point cloud to reduce the time complexity of DDE. The individuals of DDE are coded by rotation angle and the translation distance. The kd-tree is used to search for corresponding point pairs, and the root mean square error is defined as the objective function of DDE. Experiments show that the proposed method can register point clouds with a large difference in position, and has better registration accuracy than iterative closest point (ICP).

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.