Cross-Reality Map Merging With Gravity-Aligned Tracking Maps
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Solution Overview
Problem
Existing cross reality (XR) systems face challenges in accurately merging environment maps with tracking maps to maintain alignment with gravity direction, leading to distorted and less immersive user experiences.
Innovation Solution
A method for merging environment maps with tracking maps by aligning them with respect to gravity direction, using transformations that preserve the orientation of the tracking map, and discarding those that cause excessive rotation, ensuring accurate alignment and reducing merging errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If environment maps are merged with tracking maps without gravity alignment, then merging process is simpler, but alignment accuracy deteriorates
Solution Approach 1:
The system performs preliminary gravity direction determination for both environment maps and tracking maps before merging. By pre-aligning the coordinate systems to gravity direction (downward for environment maps, device orientation for tracking maps), the merging process benefits from pre-established accurate orientation relationships, improving final alignment accuracy without adding complexity during the actual merging operation.
Solution Approach 2:
The system changes the orientation parameter of the tracking map by applying a transformation to rotate it to match the gravity direction of the environment map. This parameter change (rotation to gravity-aligned orientation) enables accurate merging by ensuring both maps share the same reference frame, directly improving alignment accuracy while the transformation calculation remains computationally efficient.
2Manufacturing precision
If transformations are applied to align tracking maps with environment maps, then alignment accuracy improves, but computational cost increases
Solution Approach 1:
The system applies parameter changes by rotating the tracking map's coordinate system to match the environment map's gravity direction. This involves calculating a rotation matrix based on the gravity vectors and applying it to transform the tracking map points. The transformation is computationally efficient using standard linear algebra operations, achieving high alignment precision without excessive computational cost.
Solution Approach 2:
The system replaces complex iterative alignment algorithms with a direct analytical solution based on gravity vector comparison. Instead of using computationally intensive optimization methods, the system substitutes a straightforward mathematical approach: determining gravity directions from sensor data, computing a single rotation transformation, and applying it to align the maps. This substitution significantly reduces computational cost while maintaining high precision.
3Manufacturing precision
If tracking maps are rotated to align with gravity direction, then merging accuracy improves, but map distortion may occur
Solution Approach 1:
The system applies a rigid rotation transformation to the tracking map to change its orientation parameter to match the environment map's gravity direction. This rotation is applied uniformly across the entire map, preserving relative distances and shapes while correcting orientation. The transformation is designed to maintain the map's geometric integrity, improving merging accuracy without introducing distortion.
Data Source
AI summary
A cross reality system enables any of multiple devices to efficiently and accurately access previously persisted maps of very large scale environments and render virtual content specified in relation to those maps. The cross reality system may build a persisted map, which may be in canonical form, by merging tracking maps from the multiple devices. A map merge process determines mergibility of a tracking map with a canonical map and merges a tracking map with a canonical map in accordance with mergibility criteria, such as, when a gravity direction of the tracking map aligns with a gravity direction of the canonical map. Refraining from merging maps if the orientation of the tracking map with respect to gravity is not preserved avoids distortions in persisted maps and results in multiple devices, which may use the maps to determine their locations, to present more realistic and immersive experiences for their users.