Point Cloud Alignment Using Multiple Search Start Positions
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Solution Overview
Problem
Existing methods for aligning three-dimensional point cloud data often result in local solutions due to the presence of multiple local minima in the error function, which can lead to unsuitable coordinate transformations, especially when the error function differs from the objective function.
Innovation Solution
An alignment apparatus and method that acquire and align first and second point cloud data by setting multiple search start positions, searching for solution candidates using a preset alignment algorithm, and determining a final solution through statistical processing of these candidates, thereby stabilizing the solution and avoiding local minima.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single search start position is used for alignment, then the alignment process is simple and fast, but the solution may be a local minimum and unsuitable for coordinate transformation
Solution Approach 1:
The patent divides the alignment process into multiple independent searches starting from different initial positions. Instead of performing one alignment search, the system segments the search space by initiating multiple searches from differently displaced initial positions, then evaluates multiple solution candidates to determine the most suitable coordinate transformation.
Solution Approach 2:
The patent applies preliminary displacement actions to the initial position before starting the alignment search. By intentionally displacing the initial position by predetermined amounts in multiple directions, the system prepares multiple diverse starting points that increase the likelihood of finding a global minimum rather than getting trapped in local minima.
2Reliability
If multiple search start positions are used for alignment, then the solution reliability improves, but the alignment process becomes more complex and time-consuming
Solution Approach 1:
The patent changes the initial position parameter by applying predetermined displacements in multiple directions. By systematically varying the initial position parameter rather than keeping it fixed, the method explores different regions of the solution space while maintaining a structured approach that manages computational complexity.
Solution Approach 2:
The patent creates multiple copies of the alignment process running in parallel from different initial positions. Each copy performs the same alignment algorithm but starts from a differently displaced initial position, allowing the system to evaluate multiple solution candidates simultaneously and select the best one.
3Stability of the object's composition
If multiple search start positions are used for alignment, then the solution stability improves, but the processing time increases
Solution Approach 1:
The patent performs a limited number of additional searches with predetermined displacements rather than exhaustively searching the entire solution space. By applying a reasonable number of displacement actions (not excessive but sufficient), the system achieves stable and reliable results without incurring prohibitive computational costs.
Data Source
AI summary
An apparatus, system, method, and a control program on a recording medium are provided, each of which: acquires first point cloud data, and second point cloud data different from the first point cloud data; sets a plurality of search start positions each used for alignment form the first point cloud data to the second point cloud data; searches, for each of one or more of the plurality of search start positions, a solution candidate for coordinate transformation from the first point cloud data to the second point cloud data, to generate a plurality of solution candidates; and determines a final solution, from the plurality of solution candidates.