Point Cloud Positional Adjustment Using Rotation Axis Evaluation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
When positionally adjusting multiple groups of point cloud data, disparities occur between differences in data between point clouds in the rotation axis directions of measurement devices and differences in data between point clouds in directions perpendicular to the rotation axis, leading to inefficiencies in positional adjustment.
Innovation Solution
A measurement device and information processing device that acquire point cloud data, determine a rotation axis, and calculate positional adjustment parameters using an evaluation function that represents the desirability of positional adjustment results, optimizing the alignment of point clouds by utilizing disparities in data differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional positional adjustment methods are used to align multiple groups of point cloud data, then the adjustment process becomes computationally intensive and time-consuming, but the method fails to efficiently utilize the inherent disparities between differences in data in rotation axis directions versus directions perpendicular to the rotation axis
Solution Approach 1:
The patent segments the positional adjustment problem into two distinct components: adjustment in the rotation axis direction and adjustment in directions perpendicular to the rotation axis. By treating these directions separately and independently, the method exploits the inherent disparity in data differences between these directions, thereby reducing computational complexity and improving adjustment efficiency without sacrificing accuracy.
2Measurement precision
If traditional plane alignment methods are applied to correct height differences between point clouds, then the method can achieve basic alignment, but it cannot efficiently handle the anisotropic nature of measurement errors where rotation axis direction differences are minimal compared to perpendicular direction differences
Solution Approach 1:
The patent applies different adjustment strategies to different spatial directions based on the local characteristics of measurement errors. In the rotation axis direction where data differences are minimal, a simpler adjustment approach is used. In directions perpendicular to the rotation axis where data differences are significant, a more robust adjustment method is applied. This directional differentiation optimizes both precision and algorithmic simplicity.
Data Source
AI summary
A measurement device acquires first point cloud data at a first measurement position and second point cloud data at a second measurement position; determines a rotation axis for positional adjustment; determines, based on the rotation axis, the first point cloud data, and the second point cloud data, an evaluation function indicating a region that is a union set of one or more columnar bodies as an evaluation function representing desirability of a positional adjustment result; and calculates a positional adjustment parameter that optimizes the evaluation function based on the rotation axis, the first point cloud data, and the second point cloud data.