Sparse Volumetric Path Planning with Multi-Level Voxel Detail
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Solution Overview
Problem
Current computing systems face challenges in processing large 3D data sets efficiently, particularly in augmented and mixed reality applications, due to constraints in memory, processing resources, and the need for high-frame rates, which can lead to latency and motion sickness issues.
Innovation Solution
The implementation of a sparse volumetric data structure, such as a Sparse Sexaquaternary Tree (SST), that allows for the representation of 3D objects using voxels, where empty space is culled, reducing storage and processing requirements, and enabling hardware acceleration for real-time updates in 3D rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If dense volumetric data structures are used to represent 3D environments, then complete spatial information is available, but memory consumption and processing time increase significantly
Solution Approach 1:
The patent applies local quality by making different regions of the volumetric data have different levels of detail. Frequently viewed or important regions are represented with high detail, while less important regions use coarser representation. This allows the system to maintain spatial information completeness in critical areas while reducing overall memory consumption through selective detail distribution.
Solution Approach 2:
The patent segments the volumetric data into multiple levels of detail or resolutions. Instead of representing the entire 3D space at maximum detail, the space is divided into regions that can be independently processed and stored at appropriate detail levels, significantly reducing total memory requirements while preserving necessary spatial information.
2Manufacturing precision
If high-resolution volumetric data is processed in real-time, then rendering quality is improved, but processing speed decreases due to computational complexity
Solution Approach 1:
The patent implements dynamic adjustment of volumetric data resolution based on viewing distance, camera position, and scene importance. As the viewer moves through the environment, the system dynamically updates which regions are rendered at high resolution and which use lower resolution, allowing real-time processing while maintaining rendering quality where it matters most.
Solution Approach 2:
The patent applies partial action by processing and rendering only the portions of the volumetric data that are currently visible or relevant to the user's viewpoint. Instead of processing the entire high-resolution dataset, the system focuses computational resources on partial regions, achieving acceptable rendering quality while dramatically improving processing speed.
3Measurement precision
If complete volumetric maps are maintained for accurate pathfinding, then navigation accuracy is improved, but memory requirements and update latency increase
Solution Approach 1:
The patent maintains high-precision volumetric data only in regions relevant to the current navigation task and robot position. As the robot moves, the system selectively updates and maintains detailed maps of newly encountered spaces while using coarser or previously stored data for distant regions, reducing memory requirements and update latency while preserving navigation accuracy in critical areas.
Data Source
AI summary
A view of geometry captured in image data generated by an imaging sensor is compared with a description of the geometry in a volumetric data structure. The volumetric data structure describes the volume at a plurality of levels of detail and includes entries describing voxels defining subvolumes of the volume at multiple levels of detail. The volumetric data structure includes a first entry to describe voxels at a lowest one of the levels of detail and further includes a number of second entries to describe voxels at a higher, second level of detail, the voxels at the second level of detail representing subvolumes of the voxels at the first level of detail. Each of these entries include bits to indicate whether a corresponding one of the voxels is at least partially occupied with the geometry. One or more of these entries are used in the comparison with the image data.