Master Clock Synchronization for Multi-Sensor VR Data Alignment
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Solution Overview
Problem
Existing virtual reality and augmented reality systems face challenges in generating real-time, three-dimensional computer simulations of real environments, particularly in synchronizing multiple sensors to accurately position and orient computer-generated objects within real-time scenes.
Innovation Solution
A multi-sensing apparatus that combines synchronous and asynchronous sensors, synchronizing data from asynchronous sensors with data frames provided by synchronous sensors, using a master clock to ensure simultaneous operation and data alignment across multiple sensing devices, allowing for the creation of a real-time, immersive 3D environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple sensors are used to capture 3D data from different sources, then the comprehensiveness and immersion of the virtual reality environment is improved, but the synchronization difficulty and system complexity increase
Solution Approach 1:
The patent introduces a master clock as an intermediary time reference that all sensors (depth sensors, RGB sensors, IMUs) synchronize to. This master clock acts as a mediator that coordinates data collection across multiple sensor types, enabling comprehensive 3D capture while managing synchronization complexity through a centralized timing mechanism.
Solution Approach 2:
The system uses a universal time reference (master clock) that serves all sensor types simultaneously. This single timing mechanism coordinates depth sensors, RGB cameras, and inertial measurement units, allowing the system to handle multiple sensor functions through a unified synchronization approach rather than requiring separate synchronization systems for each sensor type.
2Measurement precision
If asynchronous sensors (such as IMUs) are used to capture continuous motion data, then the accuracy of motion tracking is improved, but the difficulty of synchronizing with frame-based synchronous sensors increases
Solution Approach 1:
The system performs preliminary action by having asynchronous sensors (IMUs) continuously collect and buffer motion data before it is needed for rendering. The IMUs operate independently and accumulate data in advance, so when synchronization is required with frame-based sensors, the data is already prepared and can be easily associated with the corresponding frame timestamp without complex real-time synchronization.
Solution Approach 2:
The patent segments the data handling process by treating asynchronous sensor data and synchronous sensor data separately. Asynchronous data from IMUs is collected continuously and segmented into buffers, while synchronous data from depth and RGB sensors is collected in discrete frames. This segmentation allows each data type to be processed according to its natural rhythm while being combined through a common timestamp reference.
3Measurement precision
If synchronous sensors with external clocking are used to ensure data alignment, then the synchronization precision is improved, but the device complexity and setup requirements increase
Solution Approach 1:
The patent merges the clocking functions by having depth sensors and RGB sensors share a common external clock source. Instead of requiring separate synchronization systems for each sensor type, the system combines their timing references to a single external clock, simplifying the overall system architecture while maintaining precise synchronization between all frame-based sensors.
4Productivity
If real-time processing of multi-sensor data is implemented, then the productivity and responsiveness of the VR system is improved, but the computational complexity and data processing requirements increase
Solution Approach 1:
The system implements periodic action by organizing data collection and processing around fixed frame timestamps from synchronous sensors. Depth sensors, RGB sensors, and IMU data are all collected and processed in periodic cycles synchronized to the frame rate. This periodic structure enables real-time processing by breaking down continuous data streams into manageable discrete units that can be handled at predictable intervals.
Data Source
AI summary
A Holocam Orb system uses multiple Holocam Orbs (Orbs) within a real-life environment to generate an artificial reality representation of the real-life environment in real time. Each Orb is an electronic and software unit that includes a local logic module, a local CPU and multiple synchronous and asynchronous sensors, include stereo cameras, time-of-flight sensors, inertial measurement units and a microphone array. Each Orb synchronizes itself to a common master clock, and packages its asynchrony data into data bundles whose timings are matched to frame timing of synchronous sensors, and all gathered data bundles and data frames are given a time stamp using a reference clock common to all Orbs. The overlapping sensor data from all the Orbs is combined to create the artificial reality representation.