UAV Camera Orientation Calibration for 3D Object-Relative Navigation
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) face challenges in accurately controlling their trajectory and orientation relative to external objects due to limited accuracy in relative image capture device calibration, which affects their ability to navigate and avoid obstacles effectively.
Innovation Solution
The implementation of a system that includes both fixed and adjustable orientation image capture devices, with a processor that uses feature correlation data to calibrate the relative orientation of the adjustable device, allowing for the determination of a three-dimensional orientation of external objects and subsequent control of the UAV's trajectory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If relative image capture device calibration is performed using traditional methods, then the calibration process is simple, but the accuracy of relative object orientation data is insufficient
Solution Approach 1:
The calibration system is segmented into multiple independent components: a fixed orientation image capture device and an adjustable orientation image capture device. This segmentation allows each device to be calibrated independently and then combined through feature correlation, improving overall measurement precision while maintaining manageable system complexity through modular design
Solution Approach 2:
Feature correlation data serves as an intermediary element that bridges the fixed and adjustable image capture devices. By using shared features visible in both device images, the system establishes accurate relative orientation relationships without requiring direct complex calibration between the devices, thereby improving accuracy while keeping the calibration process feasible
2Measurement precision
If a single image capture device is used, then the device structure is simple, but the ability to determine three-dimensional orientation relative to external objects is limited
Solution Approach 1:
The system transitions from two-dimensional image capture to three-dimensional orientation determination by introducing a second image capture device with adjustable orientation. This dimensional enhancement allows the system to capture spatial relationships from multiple angles, enabling accurate 3D orientation calculation through feature correlation between the two devices
Solution Approach 2:
The adjustable orientation image capture device serves multiple functions: it can be positioned at different orientations to capture images from various angles, and its images are used both for feature correlation with the fixed device and for determining three-dimensional object orientation. This multi-functionality maximizes the utility of each device while achieving 3D measurement capabilities
Data Source
AI summary
Controlling an unmanned aerial vehicle may include obtaining a first image from a fixed orientation image capture device of the unmanned aerial vehicle, obtaining a second image from an adjustable orientation image capture device of the unmanned aerial vehicle, obtaining feature correlation data based on the first image and the second image, obtaining relative image capture device orientation calibration data based on the feature correlation data, the relative image capture device orientation calibration data indicating an orientation of the adjustable orientation image capture device relative to the fixed orientation image capture device, obtaining relative object orientation data based on the relative image capture device orientation calibration data, the relative object orientation data representing a three-dimensional orientation of an external object relative to the adjustable orientation image capture device, and controlling a trajectory of the unmanned aerial vehicle in response to the relative object orientation data.