3D Map Optimization via Grouped Feature Triangulation
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Solution Overview
Problem
Conventional SLAM systems face complexity and high processing costs due to the need for extensive optimization of all image points in three-dimensional environment mapping, which slows down the determination of accurate maps.
Innovation Solution
A method that optimizes three-dimensional positions of characteristic elements in groups rather than individually, using image analysis and neural networks to identify and triangulate common elements, minimizing an error variable based on distance between detected and estimated positions, thereby simplifying the optimization process and reducing processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If optimization is performed for all characteristic elements in the image, then manufacturing precision of the three-dimensional map is improved, but device complexity and processing time increase significantly
Solution Approach 1:
The patent segments the set of all characteristic elements into multiple groups, where each group corresponds to a specific object in the three-dimensional environment. Instead of optimizing all elements simultaneously, the optimization is performed separately for each group, reducing the computational complexity while maintaining the precision of the three-dimensional map reconstruction.
2Manufacturing precision
If optimization is performed for all characteristic elements, then manufacturing precision of the three-dimensional map is improved, but processing time increases
Solution Approach 1:
By dividing characteristic elements into object-based groups, the patent enables parallel processing of different groups, significantly reducing the overall processing time while maintaining map precision.
Solution Approach 2:
The patent applies optimization selectively to groups of characteristic elements that require it, rather than uniformly optimizing all elements. This partial action approach reduces computational overhead while maintaining sufficient precision for the three-dimensional map.
3Productivity
If groups of characteristic elements are used for optimization, then processing time is reduced, but measurement precision may be compromised
Solution Approach 1:
The patent applies different optimization strategies to different groups of characteristic elements based on their local characteristics and the nature of the objects they represent. This allows maintaining high precision for critical elements while using faster processing for less critical groups, balancing speed and accuracy.
Data Source
AI summary
A device, a mapping system, and a method for determining a map of a three-dimensional environment including objects determine common characteristic elements in first and second images of the environment, determine groups of characteristic elements by an image analysis such that each group of characteristic elements corresponds to an object of the environment, estimate a three-dimensional position of the characteristic elements based on a triangulation between positions of the characteristic elements in the first image and positions of the corresponding characteristic elements in the second image, and, for each group of characteristic elements, optimize the three-dimensional positions of the characteristic elements of the respective group by minimizing an error variable which is a function, for all the characteristic elements of the group, of a distance between a detected position of the characteristic elements from at least the first image and a two-dimensional position associated with the corresponding estimated three-dimensional position.