UAV Visual Marker Localization for Low-Power Absolute Positioning
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Solution Overview
Problem
Existing localization systems for mobile devices, such as UAVs and land vehicles, face challenges in providing accurate and efficient absolute position data in real-time, particularly due to power and weight constraints, robustness issues, and interference from noise and distortion, which affects their ability to control movements effectively.
Innovation Solution
A localization system with onboard sensors and redesigned markers that include a fixed pattern and a variable data area, allowing for efficient detection and processing of markers in a single scan direction, even at various angles, and utilizing a processor to determine absolute positions using marker data from multiple markers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional onboard localization systems are used, then absolute position data can be obtained, but power consumption increases and weight constraints are violated
Solution Approach 1:
The patent replaces complex onboard localization hardware (accelerometers, gyroscopes, barometers) with a simpler visual marker detection system using image processing algorithms. This substitution dramatically reduces power consumption while maintaining localization accuracy, as the system uses the device's existing camera and processes images through optimized algorithms that track marker positions and calculate device location.
Solution Approach 2:
The patent uses visual markers as external references that the device camera captures and processes. Instead of relying on expensive onboard sensors, the system creates a digital copy of the physical environment through marker detection and uses this visual information to determine absolute position, thereby reducing hardware requirements and power consumption.
2Measurement precision
If traditional onboard localization systems are used, then position information can be obtained, but weight of the mobile device increases
Solution Approach 1:
The patent eliminates heavy onboard localization hardware by substituting it with software-based marker detection and image processing. The system uses the device's existing camera and computational resources to achieve accurate positioning without adding significant weight, making it ideal for mobile devices where weight constraints are critical.
Solution Approach 2:
The patent extracts the localization function from the mobile device itself and places it in the external environment through visual markers. By moving the localization reference system from onboard sensors to external markers, the device weight is minimized while maintaining positioning capability.
3Productivity
If standard marker detection methods are used, then markers can be detected, but detection accuracy decreases due to noise and distortion
Solution Approach 1:
The patent segments the marker detection process into distinct stages: preprocessing to remove noise, edge detection to identify marker boundaries, pattern recognition to identify marker types, and coordinate calculation to determine position. This segmentation allows each stage to be optimized independently, maintaining both speed and accuracy even in noisy conditions.
Solution Approach 2:
The patent applies preliminary image preprocessing operations (noise filtering, contrast enhancement, edge detection) before marker detection. This preliminary action prepares the image data to be more robust against noise and distortion, enabling accurate and fast detection even in challenging environments.
4Speed
If fast localization is implemented for real-time control, then responsiveness improves, but robustness to interference and distortion decreases
Solution Approach 1:
The patent segments the localization process into optimized stages with different computational complexities. The preprocessing and marker identification stages are designed for speed to maintain real-time performance, while the coordinate calculation and verification stages incorporate robustness checks. This segmentation allows the system to achieve both fast response and resistance to interference.
Solution Approach 2:
The patent implements feedback mechanisms where detected marker positions are continuously verified and adjusted based on expected patterns and previous positions. This feedback loop allows the system to maintain fast localization speeds while correcting for noise and distortion, thereby improving robustness without sacrificing real-time performance.
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
The system provides robust and efficient localization, reducing power consumption, improving detection accuracy, and maintaining information integrity, enabling precise control of mobile devices in dynamic environments.
Implementation Method 1
A camera provided on the mobile device captures a plurality of images of the travel space
Data Source
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AI summary
A method for facilitating determination of positions of mobile devices within an operating space containing a number of objects, the method comprising placing at least three markers on exposed surfaces of the objects, wherein each of the markers includes a pattern of linear bars adjacent a data area, wherein the pattern of linear bars is identical on each of the markers and the data area has a pattern that varies between the markers; and operating a mobile device to move about the operating space in response to control signals; the method further comprising the steps, performed at the mobile device of using a single direction scan of an image to locate the markers in the image, wherein at least one of the markers is positioned to be oriented in the image such that the pattern of linear bars is non-orthogonal to the single direction scan; extracting data from the pattern of the data areas; estimating the position of the mobile device based on the extracted data; and generating the control signals based on the estimated position of the mobile device within the operating system.