SLAM Landmark Backchannel Encoding for Bandwidth-Limited xR
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Solution Overview
Problem
In virtual, augmented, or mixed reality applications, connectivity-constrained environments pose challenges for efficient data transmission and processing, particularly in Head-Mounted Devices (HMDs) that lack sufficient processing capacity, leading to mapping and tracking errors due to data loss and delayed transmission of Simultaneous Localization and Mapping (SLAM) data.
Innovation Solution
The implementation of backchannel encoding methods in HMDs, where SLAM landmarks are encoded based on distance to the device using different compression parameters, and transmitted to an Information Handling System (IHS), with adaptive Look-Up Tables (LUTs) selected based on context information and data loss metrics to optimize data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SLAM landmarks are transmitted with high precision and low compression, then mapping and tracking accuracy is improved, but data transmission bandwidth and processing requirements increase beyond what connectivity-constrained environments can provide
Solution Approach 1:
The patent applies local quality by encoding SLAM landmarks with different compression parameters based on their distance from the HMD. Nearby landmarks (within threshold distance) use first compression parameters that preserve higher precision, while distant landmarks use second compression parameters with higher compression. This resolves the contradiction by allocating transmission resources selectively - maintaining high precision for critical nearby landmarks while reducing data volume for less critical distant landmarks.
Solution Approach 2:
The patent changes encoding parameters dynamically based on landmark distance. The system selects from multiple compression parameter sets (first parameters for nearby landmarks, second parameters for distant landmarks) to optimize the balance between precision and data volume. This parameter adaptation allows the system to maintain acceptable mapping and tracking accuracy while significantly reducing overall data transmission requirements for connectivity-constrained environments.
2Productivity
If the HMD performs extensive encoding and processing of SLAM data, then data transmission efficiency is improved, but the HMD's limited processing capability is exceeded
Solution Approach 1:
The patent segments the SLAM landmark data processing task by dividing landmarks into two categories based on distance: nearby landmarks (within threshold distance) and distant landmarks. This segmentation allows the HMD to apply different, optimized encoding strategies for each group, improving overall transmission efficiency without requiring the HMD to handle all landmarks with the most computationally intensive methods.
Solution Approach 2:
The patent applies partial action by performing encoding operations only on the most critical nearby landmarks with high-priority compression parameters, while applying more aggressive compression to distant landmarks. This selective approach ensures that the HMD's limited processing capabilities are focused on preserving accuracy for nearby landmarks that matter most for immediate tracking, while still transmitting sufficient information about distant landmarks without exceeding processing limits.
3Productivity
If compression parameters are adjusted based on distance, then data transmission is optimized for connectivity-constrained environments, but mapping precision for distant landmarks deteriorates
Solution Approach 1:
The patent applies local quality by implementing distance-based differential encoding: landmarks within a threshold distance use first compression parameters that maintain high precision, while landmarks beyond the threshold use second compression parameters with higher compression ratios. This resolves the contradiction by ensuring that precision is maintained locally for nearby landmarks where it matters most for accurate tracking and mapping, while accepting reduced precision for distant landmarks that have less impact on immediate navigation performance.
Solution Approach 2:
The patent changes compression parameters based on landmark distance from the HMD. The system dynamically selects between multiple parameter sets stored in look-up tables, switching from first parameters (lower compression, higher precision) for nearby landmarks to second parameters (higher compression, lower precision) for distant landmarks. This parameter adaptation optimizes the trade-off between transmission efficiency and precision, ensuring acceptable performance in connectivity-constrained environments.
Data Source
AI summary
Embodiments of systems and methods for backchannel encoding in virtual, augmented, or mixed reality (xR) applications in connectivity-constrained environments are described. In some embodiments, an Head-Mounted Device (HMD) may include a processor; and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution by the processor, cause the HMD to: encode each of a plurality of Simultaneous Localization and Mapping (SLAM) landmarks, in part, based upon the SLAM landmark's distance to the HMD; and transmit the encoded SLAM landmarks to an Information Handling System (IHS) coupled to the HMD.