AR Headset Object Tracking via Multi-Sensor Fusion
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Solution Overview
Problem
Current AR/MR/XR devices lack the ability to provide sufficient feedback for complex and highly sensitive workflows, such as laboratory procedures, due to inadequate object identification, localization, and pose determination, which limits their ability to interpret the user's activity, workspace, and artifact configurations over time.
Innovation Solution
An interactive procedural system that uses a combination of sensors like cameras, time of flight sensors, structured illumination sensors, and LIDAR to accurately determine the location, type, and pose of objects within the user's field of view, and updates the virtual skin displayed to the user based on these determinations, enabling precise spatial tracking and interpretation of physical and virtual objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If present AR/MR/XR applications are used for procedural guidance, then basic object recognition is achieved, but sufficient feedback for complex and highly sensitive workflows cannot be provided
Solution Approach 1:
The system segments object recognition into multiple levels: basic object identification, detailed pose determination, and contextual interpretation. Each sensor type (camera, ToF, structured illumination, LIDAR) segments the information gathering process, capturing different aspects of the workspace independently before integrating them for comprehensive feedback.
Solution Approach 2:
The AR/MR/XR system is enhanced with multiple sensor types that serve universal functions across different workflow complexities. The same sensor suite used for basic object recognition also enables pose determination, spatial tracking, and contextual interpretation, allowing a single system to handle both simple and highly sensitive workflows effectively.
2Adaptability or versatility
If basic object recognition is implemented, then simple workflows can be supported, but complex workflows requiring pose and motion tracking cannot be handled
Solution Approach 1:
The system merges data from multiple sensor types (camera, time of flight sensor, structured illumination sensor, LIDAR) to achieve both versatility across workflow complexities and high measurement precision. By combining these sensors, the system simultaneously supports simple object recognition and complex pose/motion tracking with accurate spatial information.
Solution Approach 2:
The system transitions from two-dimensional image recognition to three-dimensional spatial understanding by incorporating depth information from ToF sensors, structured illumination sensors, and LIDAR. This dimensional enhancement enables accurate pose determination and motion tracking while maintaining adaptability to various workflow complexities.
3Ease of operation
If present AR/MR/XR systems are configured to recognize objects, then basic identification is achieved, but interpretation of sensitive scenarios and consequences cannot be provided
Solution Approach 1:
The system implements multi-level feedback: first providing basic object identification feedback, then layering additional feedback about pose, spatial relationships, and contextual consequences. This progressive feedback mechanism maintains ease of operation for simple tasks while providing comprehensive contextual interpretation for sensitive scenarios when needed.
Solution Approach 2:
The system performs preliminary actions by continuously gathering comprehensive sensor data and pre-interpreting workspace configurations before users need the information. This allows the system to have contextual understanding and consequence interpretation ready in advance, maintaining ease of operation while preventing information loss during critical moments.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enhances the fidelity and resolution of feedback for complex workflows by enabling accurate localization, pose determination, and tracking of physical objects, allowing for safer and more precise execution of procedures by highlighting potential hazards and providing contextual guidance.
Implementation Method 1
receiving, by an interactive procedural system, first sensor data that reflects first characteristics of an environment where a user wearing an augmented, mixed, or extended reality (AR/MR/XR) headset is located; based on the first sensor data, determining, by the interactive procedural system, a location of an object
Implementation Method 2
receiving, by an interactive procedural system, first sensor data that reflects first characteristics of an environment where a user wearing an augmented, mixed, or extended reality (AR/MR/XR) headset is located; based on the first sensor data, determining, by the interactive procedural system, a location of an object within a field of view of the AR/MR/XR headset
Implementation Method 3
receiving, by an interactive procedural system, first sensor data that reflects first characteristics of an environment where a user wearing an augmented, mixed, or extended reality (AR/MR/XR) headset is located; based on the first sensor data, determining, by the interactive procedural system, a location of an object
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, directed to an interactive procedural guidance system are disclosed. In one aspect, a method includes the actions of receiving, by an interactive procedural system, first sensor data that reflects first characteristics of an environment where a user wearing an augmented, mixed, or extended reality headset is located. The actions further include determining a location of an object within a field of view of the AR/MR/XR headset. The actions further include identifying a type of the object. The actions further include determining a skin that is configured to be displayed to the user through the headset over the object. The actions further include receiving second sensor data that reflects second characteristics of the environment. The actions further include determining that an event has occurred with respect to the object. The actions further include updating the skin.