3D Mapping Data Projection for UAV Bandwidth Reduction
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Solution Overview
Problem
Existing systems for mapping data collected by movable objects, such as UAVs, are inefficient due to the complexity of processing and rendering large amounts of 3D mapping data, which can lead to incomplete mapping, high data storage requirements, and increased processing time.
Innovation Solution
The method involves generating representation data by projecting 3D mapping data onto a 2D plane based on a selected perspective of view, allowing for the creation of a smaller, more manageable image preview that can be easily stored and transmitted, while still maintaining the original 3D data format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 3D mapping data is processed and rendered in full detail, then mapping completeness is improved, but processing time and data storage requirements increase significantly
Solution Approach 1:
The patent segments mapping data into multiple resolutions (first resolution with sparse points, second resolution with dense points). This allows the system to process and render lower-resolution data for quick visualization while maintaining access to higher-resolution data for detailed analysis, thereby reducing processing time without completely sacrificing mapping completeness.
Solution Approach 2:
The patent implements partial processing by generating representation data at a first resolution that covers the entire mapping area with sparse points, and only processes dense points at a second resolution for specific regions of interest. This partial action approach reduces overall processing time while maintaining necessary mapping completeness for the full area.
2Measurement precision
If high-resolution 3D mapping data is stored and transmitted, then data accuracy is improved, but data communication bandwidth and storage requirements increase
Solution Approach 1:
The patent segments mapping data into multiple resolution levels. The first resolution data provides coverage of the entire mapping area with reduced point density, while the second resolution data provides high accuracy only for specific regions. This segmentation reduces the total quantity of data that needs to be stored and transmitted while maintaining measurement precision where needed.
Solution Approach 2:
The patent applies local quality by providing high-resolution dense points only for specific regions of interest rather than uniformly across the entire mapping area. The majority of the mapping area uses lower-resolution sparse points, which reduces the overall data volume while maintaining high data accuracy locally where it is most needed.
3Reliability
If full 3D mapping data is rendered on client devices, then rendering completeness is improved, but device processing load and rendering time increase
Solution Approach 1:
The patent segments rendering data into two resolution levels. The first resolution representation data with sparse points is used for rendering the overall mapping scene, providing rendering completeness. The second resolution dense points are used selectively for detailed views or regions of interest, improving rendering efficiency by avoiding the need to process all high-resolution data for every rendering operation.
Solution Approach 2:
The patent implements partial rendering by transmitting and rendering first resolution sparse point data for the entire mapping area, and only processing second resolution dense point data when specific detailed views are required. This partial action approach improves rendering efficiency while maintaining rendering completeness for the overall scene.
Data Source
AI summary
Techniques are disclosed for generating representation data of mapping data in a movable object environment. A method of generating representation data of three-dimensional mapping data may include: receiving three-dimensional mapping data captured by a sensor; generating representation data by projecting the three-dimensional mapping data onto a two-dimensional plane based on a selected perspective of view; and associating the representation data with the three-dimensional mapping data.