Adaptive AR Environment Refresh Rate for Power and Accuracy Balance
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Solution Overview
Problem
Existing augmented reality (AR) systems lack control over the environment-computation refresh rate, leading to inefficient resource usage and suboptimal user experiences due to fixed computation rates that do not adapt to changing user and environmental conditions.
Innovation Solution
Implement a mechanism that allows user equipment to dynamically adjust the environment-computation refresh rate based on factors such as user movement, environment evolution, network conditions, and battery life, using metadata provided by XR content creators to manage resource usage and enhance user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the environment-computation refresh rate is increased to improve AR experience quality, then user experience and rendering accuracy are improved, but resource consumption and power usage increase
Solution Approach 1:
The patent applies dynamics by making the environment-computation refresh rate adjustable rather than fixed. The system dynamically adapts the refresh rate based on real-time factors including user movement speed, battery charge level, network conditions, and environment evolution rate. This allows the system to optimize between AR experience quality and power consumption by increasing the refresh rate only when necessary (e.g., during rapid user movement or when battery is fully charged) and decreasing it during stable conditions.
Solution Approach 2:
The patent implements parameter changes by modifying the refresh rate parameter based on multiple input conditions. The system changes the refresh rate parameter dynamically according to detected user movement velocity, battery charge percentage, network bandwidth availability, and environmental change rate. This enables the system to adjust computational intensity to match actual usage requirements, thereby optimizing the trade-off between AR quality and energy consumption.
2Device complexity
If the environment-computation refresh rate is fixed to simplify system design, then device complexity is reduced, but adaptability to changing conditions deteriorates
Solution Approach 1:
The system transitions from a static fixed refresh rate to a dynamic adaptive refresh rate mechanism. While this increases some system complexity, it enables the system to automatically adjust to changing conditions such as user movement speed, battery level, and network conditions without manual intervention, thereby improving adaptability significantly.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors multiple parameters including user movement velocity, battery charge level, network bandwidth, and environment evolution rate. Based on this feedback, the system automatically adjusts the refresh rate to optimize performance for current conditions, enabling the system to adapt to varying scenarios dynamically.
3Measurement precision
If the environment-computation refresh rate is increased to improve localization accuracy, then AR rendering accuracy is improved, but computation time and processing load increase
Solution Approach 1:
The system dynamically adjusts the refresh rate based on the current situation. During periods of high user movement or when high localization accuracy is critical, the system increases the refresh rate to maintain precision. During stable periods with lower movement, the system reduces the refresh rate to minimize computation time and processing load, thereby optimizing the trade-off between accuracy and time efficiency.
Solution Approach 2:
The system employs periodic evaluation of conditions (user movement detection, battery level monitoring, network status checks) to determine when to adjust the refresh rate. This periodic action allows the system to maintain high accuracy when needed while reducing computation during stable periods, balancing precision requirements with processing efficiency.
Data Source
AI summary
Example embodiments provide a mechanism enabling a user equipment, UE, to adapt the environment-computation refresh rate to improve user extended reality, XR, experience and limit resource usage. An example method includes obtaining sensor data describing a user's environment: obtaining information indicating at least one factor from among: user movement information, environment evolution information, network condition information, or battery life information: determining a candidate environment-computation refresh rate based on the at least one factor: selecting an environment-computation refresh rate as a minimum of: the candidate environment-computation refresh rate and a maximum environment-computation refresh rate; and updating a real-environment computation using the selected environment-computation refresh rate.


