In this paper a system for the detection and research of archaeological sites using on machine learning methods, mapping methods and geophysics methods is presented. The development of an information system for remote archaeological research allows, on the one hand, to solve the most important problem of archaeological science, related to the preservation of cultural heritage, and on the other hand, to reduce the duration of the archaeological examination procedure conducted before the industrial development of the territory. In this paper the method for registering 3D data based on ICP (Iterative Closest Points) based on fusion of visual and semantic characteristics of an archaeological site for a class of orthogonal transformations was proposed. Computer modeling of the proposed 3d registration method was carried out using a collection of data from archaeological sites of the Bronze Age of the Southern Trans-Urals. When performing computer modeling, methods for solving the variational ICP problem were considered, using various options for minimizing the functional: the point-to-point metric with and without extrapolation, using the point-to-plane metric. A comparative analysis with various options for minimizing the functional was carried out, the results of computer simulation were presented and discussed.