LiTAMIN: LiDAR-based Tracking And Mapping by Stabilized ICP for Geometry Approximation with Normal Distributions
Masashi Yokozuka,Kenji Koide,Shuji Oishi,Atsuhiko Banno,Masashi Yokozuka,Kenji Koide,Shuji Oishi,Atsuhiko Banno
This paper proposes a 3D LiDAR simultaneous localization and mapping (SLAM) method that improves accuracy, robustness, and computational efficiency for an iterative closest point (ICP) algorithm employing a locally approximated geometry with clusters of normal distributions. In comparison with previous normal distribution-based ICP methods, such as normal distribution transformation and generalize...
