Point Cloud Alignment in Mixed Reality Floor Visualization
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Solution Overview
Problem
Conventional methods for aligning graphical representations of point clouds with environments are insufficient, making it difficult to accurately locate problematic areas in the physical world, especially when using augmented reality, as they lack effective localization of point clouds within the environment.
Innovation Solution
The method involves using point alignment and movement alignment techniques to align a point cloud with a floor plan or video stream by selecting virtual points and corresponding environmental points, and adjusting the point cloud's position to minimize distances between these points, utilizing simultaneous localization and mapping algorithms and augmented reality to enhance visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods for aligning point clouds with environments are used, then the basic visualization can be achieved, but the localization accuracy is insufficient and it becomes difficult to accurately locate problematic areas in the physical world
Solution Approach 1:
The patent introduces floor plan images and video streams as intermediary reference frames to bridge the point cloud data with the physical environment. By aligning point clouds with these intermediary references rather than directly with the physical world, the system achieves accurate localization while maintaining ease of operation through automated alignment processes.
Solution Approach 2:
The patent replaces manual alignment methods with automated computer vision algorithms that process images and video streams to establish correspondences between point cloud features and environmental features. This substitution of mechanical/manual alignment with automated computational methods significantly improves localization accuracy while reducing operational complexity.
2Measurement precision
If point alignment techniques are applied to improve localization, then the accuracy of locating problematic areas improves, but the complexity of the alignment process increases
Solution Approach 1:
The patent segments the alignment process into distinct stages: first aligning point clouds with floor plan images, then aligning the results with video streams. This segmentation allows each alignment operation to focus on a specific reference type, reducing the overall computational complexity while maintaining high localization accuracy through cumulative precision.
Solution Approach 2:
The patent performs preliminary alignment with floor plan images before incorporating video stream alignment. This preliminary action establishes a solid foundational alignment that simplifies subsequent video stream alignment operations, as the point cloud is already partially localized relative to the environment through the floor plan reference.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves the visualization of point clouds in augmented reality environments by accurately overlaying 3D measurement data onto images or video streams, providing a clear visual indication of scan-point coverage, floor flatness, and defect detection, enabling users to better understand the environment through enhanced contextual information.
Implementation Method 1
A 3D laser scanner of this type steers a beam of light to a non-cooperative target such as a diffusely scattering surface of an object. A distance meter in the device measures a distance to the object
Implementation Method 2
A 3D laser scanner of this type steers a beam of light to a non-cooperative target
Data Source
AI summary
Described herein are systems and methods for point cloud alignment with a floor plan or a video stream of an environment. The systems and method comprise overlaying a graphical representation of a point cloud onto an image of the floor plan and the video stream. The systems and methods further comprise aligning the graphical representation of the point cloud and the image of the floor plan with the video stream using a point alignment. The systems and methods further comprise displaying an update of the graphical representation based at least in part on a further point alignment or a movement alignment.