Graph Optimization for Multi-Station Point Cloud Registration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for multi-view point cloud registration of large-size objects like aircrafts are inefficient due to repeated pair-wise registration, leading to high computational load and accumulated registration errors, making it difficult to achieve accurate and precise measurements.
Innovation Solution
A multi-station scanning global point cloud registration method based on graph optimization, which involves acquiring three-dimensional point cloud data using a three-dimensional laser scanner, performing initial registration with cross targets, calculating overlap areas, constructing a graph structure, and performing loop closure-based hierarchical registration to achieve fine registration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If repeated pair-wise registration is used for multi-view point cloud registration, then the registration process is simple to implement, but the computational load is high and registration efficiency is low
Solution Approach 1:
The patent segments the multi-view point cloud registration problem into two distinct stages: initial pair-wise registration and subsequent global optimization registration. The initial registration uses simple pair-wise methods to establish rough alignments, while the global optimization stage applies graph-based optimization to simultaneously refine all registrations. This segmentation allows the system to benefit from both the simplicity of pair-wise methods and the efficiency of global optimization.
2Ease of manufacture
If repeated pair-wise registration is used for multi-view point cloud registration, then the implementation is straightforward, but the registration error accumulates and accuracy decreases
Solution Approach 1:
The patent implements a feedback mechanism where the initial pair-wise registration results serve as input to the global optimization stage. The graph-based optimization uses the initial alignments to construct a optimization problem that minimizes cumulative registration errors across all views. This feedback loop allows the system to correct accumulated errors by considering all views simultaneously, thereby improving overall accuracy while maintaining implementation feasibility.
3Productivity
If three-dimensional laser scanning is used for acquiring point cloud data of large-size objects, then the detection efficiency is greatly increased, but the data computation becomes large and processing becomes complex
Solution Approach 1:
The patent segments the large-scale point cloud data processing into manageable stages: initial pair-wise registration to establish rough alignments, overlap region identification to focus computation on relevant areas, and graph-based global optimization to refine registrations. This segmentation reduces the computational complexity by avoiding direct processing of all data points across all views simultaneously, while still achieving high detection efficiency through the rapid initial registration stage.
Data Source
AI summary
Disclosed a multi-station scanning global point cloud registration method based on graph optimization, including acquiring multi-station original three-dimensional point cloud data; based on initial registration of targets, completing initial registration of point cloud data at adjacent stations by virtue of the target at each angle of view; calculating a point cloud overlap area at adjacent angles of view, and calculating areas of overlap regions of adjacent point cloud by a gridded sampling method; constructing a fine registration graph structure, and constructing a fine registration graph by taking point cloud data of each station as a node of the graph and taking an overlap area of the point cloud data of adjacent stations as a side of adjacent nodes of the graph structure; and based on loop closure fine registration based on graph optimization, gradually completing point cloud fine registration of the whole aircraft according to a specific closure sequence.