This invention proposes a registration method for point clouds with low overlap rates, effectively improving upon traditional
point cloud registration methods which suffer from
slow speed, low accuracy, and poor stability. The method is based on variable data sequence length least truncated squares (LTS). For the
complete sequence obtained by ascending ordering the Euclidean distances of matching point pairs, since
pose changes after each iteration cause variations in the distance sequence of the matching point pairs, in each iteration, using the right endpoint of the
complete sequence as a reference, a dynamically changing
local sequence is selected from the
complete sequence based on the
point cloud overlap rate and the current iteration number. This changes the position of the LTS truncated sequence on the complete sequence. When the iteration termination condition is met, the maximum length of the
local sequence is the same as the length of the complete sequence. As the iteration progresses, the length of the
local sequence continuously increases, thus implementing a variable data sequence length strategy during registration. Compared with traditional
point cloud registration methods, this invention offers better speed, accuracy, and stability, especially when registering point clouds with low overlap rates, where the
performance improvement is particularly significant.