UAV Sensor Calibration via In-Flight Checker Pattern Recognition
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Solution Overview
Problem
The calibration of cameras and sensors on unmanned aerial vehicles (UAVs) is a time-consuming process, delaying their departure and affecting operational efficiency, especially in aerial navigation tasks where precise sensor calibration is crucial.
Innovation Solution
The implementation of an autonomous UAV system that verifies and adjusts camera and sensor calibration by processing images of known objects within the environment, comparing processed information with actual data, and applying software corrections or full calibration as needed, utilizing pre-flight calibration stations and channels to ensure sensor accuracy before flight.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods are used for UAV sensors, then measurement precision is improved, but loss of time increases due to the time-consuming calibration process
Solution Approach 1:
The system performs preliminary calibration actions by capturing images of known objects (checkers) during flight operations. The calibration data is collected and processed in advance, allowing the UAV to perform self-calibration without requiring separate calibration sessions, thus reducing calibration time while maintaining precision.
Solution Approach 2:
The UAV system performs self-calibration by automatically capturing images, processing the image data to detect checker patterns, and adjusting calibration parameters autonomously. This self-service approach eliminates the need for manual calibration operations, significantly reducing the time required while maintaining measurement precision.
2Reliability
If comprehensive sensor calibration is performed, then reliability of aerial navigation is improved, but device complexity increases due to multiple calibration stations and processes
Solution Approach 1:
The calibration system is designed to be multi-functional, serving both calibration and navigation purposes. The same imaging system used for navigation tasks is also used for calibration, eliminating the need for separate calibration equipment. This reduces device complexity while maintaining navigation reliability through comprehensive calibration.
Solution Approach 2:
Known objects (checkers) serve as intermediaries between the sensor system and the calibration process. These standardized objects provide reference patterns that simplify the calibration algorithm, making the system more reliable while reducing the complexity of direct sensor calibration through mathematical modeling.
3Productivity
If rapid calibration is implemented, then productivity of UAV operations is improved, but measurement precision may deteriorate due to reduced calibration thoroughness
Solution Approach 1:
The system implements periodic calibration during flight operations by capturing images of known objects at regular intervals or at specific flight phases. This periodic action ensures continuous calibration maintenance without requiring lengthy dedicated calibration sessions, thereby preserving both productivity and measurement precision.
Solution Approach 2:
The system performs partial calibration actions by focusing on critical calibration parameters using simplified algorithms for rapid processing. By applying excessive computational effort to key calibration aspects while reducing effort on less critical parameters, the system maintains adequate precision while improving overall productivity.
Data Source
AI summary
This disclosure describes systems, methods, and apparatus for automating the verification of aerial vehicle sensors as part of a pre-flight, flight departure, in-transit flight, and/or delivery destination calibration verification process. At different stages, aerial vehicle sensors may obtain sensor measurements about objects within an environment, the obtained measurements may be processed to determine information about the object, as presented in the measurements, and the processed information may be compared with the actual information about the object to determine a variation or difference between the information. If the variation is within a tolerance range, the sensor may be auto adjusted and operation of the aerial vehicle may continue. If the variation exceeds a correction range, flight of the aerial vehicle may be aborted and the aerial vehicle routed for a full sensor calibration.