Helmet-Mounted Vision-Inertial Navigation System for Wide Lighting Range
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Solution Overview
Problem
Current vision-inertial navigation systems are not suitable for military and governmental applications due to limitations in operating in a wide range of ambient lighting conditions, requiring large sensors, manual calibration, and not being wearable.
Innovation Solution
A miniature vision-inertial navigation system that includes helmet-mounted cameras and inertial sensors, with a remote processing element combining image data to estimate object positions in real-time, capable of operating from indoor to direct sunlight and low-light conditions, and featuring automatic boresight calibration and plug-and-play functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If vision-inertial navigation systems use very large sensors to operate in a wide range of ambient lighting conditions, then the system can function from indoor to direct sunlight conditions, but the system becomes too large to be wearable
Solution Approach 1:
The patent divides the imaging function into multiple specialized cameras, each optimized for specific lighting conditions (sunlight, indoor, night vision). This segmentation allows each camera to be smaller and more efficient than a single all-purpose camera would need to be, enabling the overall system to remain wearable while maintaining wide adaptability across lighting conditions.
Solution Approach 2:
The system achieves multi-functionality by integrating multiple camera types (visible light cameras for sunlight and indoor conditions, night vision cameras for low-light environments) into a single navigation system. This universal approach allows one system to handle diverse lighting conditions without requiring separate devices, maintaining compact size while providing broad operational versatility.
2Adaptability or versatility
If vision-inertial navigation systems manually perform boresight calibration and configure settings, then the system can be customized for specific applications, but the ease of operation is reduced
Solution Approach 1:
The system performs self-calibration by automatically determining the relative positions and orientations of multiple cameras and inertial sensors using visual features and motion data. This self-service capability eliminates the need for manual boresight calibration while maintaining the system's adaptability to different applications, significantly improving ease of operation.
Solution Approach 2:
The system performs preliminary automatic calibration during initial setup or boot-up, establishing the spatial relationships between sensors before actual navigation begins. This preliminary action ensures that customization capabilities are maintained while requiring no manual intervention during operation, thereby improving ease of use.
3Device complexity
If vision-inertial navigation systems use a single camera type, then the device complexity is reduced, but the system cannot function accurately across different lighting conditions
Solution Approach 1:
The patent applies local quality by assigning specific camera types to specific lighting conditions (visible light cameras for bright conditions, night vision cameras for dark conditions). Each camera is optimized for its intended environment, improving accuracy in that specific context while the overall system maintains manageable complexity through modular integration.
Solution Approach 2:
The system dynamically selects and switches between different camera types based on ambient lighting conditions. This dynamic adaptation allows the system to maintain optimal performance across varying environments without requiring all cameras to be simultaneously active, thereby managing computational complexity while achieving broad lighting condition coverage.
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
Enables accurate tracking and display of object positions in a wide range of lighting conditions, providing a compact, wearable, and user-friendly solution for tactical applications.
Implementation Method 1
inertial sensors, particularly gyroscopes and accelerometers, to estimate device pose
Data Source
AI summary
A system and method for tracking positions of objects in an actual scene in a wide range of lighting conditions. A vision-inertial navigation system is provided that may be configured to track relative positions of objects of interest in lighting conditions ranging from, e.g., typical indoor lighting conditions to direct sunlight to caves with virtually with no light. The navigation system may include two or more helmet-mounted cameras each configured to capture images of the actual scene in a different lighting condition. A remote processing element may combine data from the two or more helmet-mounted cameras with data from a helmet-mounted inertial sensor to estimate the position (e.g., 3D location) of the objects. The navigation system may display the estimated position for each object on a transparent display device such that, from a user's perspective, the estimated position for each object is superimposed onto the corresponding object and/or other information relating to the user's and/or object's position is displayed.