The invention discloses a LiDAR point cloud no-initial-value registration method based on planar feature constraint. According to the invention, expression of plane features in a three-dimensional space is realized by adopting a four-parameter method; parameters of homonymous plane features of the registered adjacent observation stations are equal to serve as constraint conditions, a three-dimensional space similarity transformation objective function based on dual quaternion description under plane feature constraint is constructed according to the least square criterion, and non-initial-value solving of the registration parameters is achieved through extreme value analysis of the objective function. The four-parameter expression of the plane features provides a simpler and more effective mode for the comparison of homonymous features; compared with a vector algebra, the spatial similarity transformation model based on dual quaternion description is simpler in expression form and fewer in additional constraint conditions in the registration process; compared with an iteration method, the algorithm has the advantages that the parameters are directly solved on the premise that the initial values of the parameters of the space similarity transformation model do not need to be determined in advance, the stability of the algorithm is better, and the reliability is higher.