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Accurate point cloud registration algorithm based on RANSAC

Published: 28 June 2024 Publication History

Abstract

Point cloud registration is widely used in robot grasping, aerial mapping, 3D reconstruction and other fields. Aiming at the problems of large pose deviation of point clouds in photographic point clouds, large noise and dense number of point clouds, it is difficult for the traditional iterative closest point (ICP) algorithm to achieve automatic registration. In order to solve the above problems, an improved precision point cloud registration method is proposed. The method includes two stages: coarse registration and fine registration, in the coarse registration stage, the point cloud is simplified by the Approximate Intrinsic Voxel Structure (AIVS) algorithm, and the simplified point cloud is initially registered by the improved RANSAC algorithm. Then, on the basis of the initial registration, a fast and accurate algorithm (FR-ICP) is used for precise registration. This method solves the problem that ICP is sensitive to initial pose. Experiments based on the self-constructed auto parts point cloud dataset show that compared with the ICP algorithm, the registration accuracy and time of the proposed method are improved by 95.8% and 67.8%, respectively.

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      ICRSA '23: Proceedings of the 2023 6th International Conference on Robot Systems and Applications
      September 2023
      335 pages
      ISBN:9798400708039
      DOI:10.1145/3655532
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Published: 28 June 2024

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