Dynamic Camera Triggering for UAV Photogrammetry
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Solution Overview
Problem
Existing photogrammetry systems using single RGB cameras on UAVs require longer flight times and more surveying time due to pre-configured camera triggering, often resulting in too few or too many images, which can lead to poor quality models and increased costs.
Innovation Solution
A photogrammetry system with multiple cameras and a processor that determines optimal trigger times based on real-time vehicle telemetry, camera specifications, and photogrammetric requirements, allowing image acquisition during vehicle movement and adjusting for environmental factors like wind speed, ensuring the right amount of images are captured.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single camera is used with pre-configured triggering, then the system is simple to operate, but the survey time is excessive and image coverage is insufficient
Solution Approach 1:
The system divides the imaging task into multiple parallel camera units instead of using a single camera. Each camera captures images simultaneously, segmenting the survey area into multiple zones that can be covered in parallel, thereby reducing total survey time while maintaining operational simplicity through centralized control.
Solution Approach 2:
The triggering configuration transitions from static pre-setting to dynamic real-time adjustment. The system dynamically determines trigger times based on actual vehicle telemetry data, camera specifications, and photogrammetric requirements during flight, allowing flexible adaptation to changing conditions without increasing operational complexity.
2Ease of manufacture
If camera triggering is pre-configured at specific locations or frequencies, then the system is easy to set up, but the image coverage is either too sparse or too dense
Solution Approach 1:
The system implements feedback by continuously monitoring vehicle telemetry data during flight and using this information to dynamically adjust camera trigger times. This closed-loop control ensures optimal image coverage quality by adapting to actual flight conditions, while the automated nature of the feedback process maintains ease of setup.
Solution Approach 2:
The system changes the triggering parameter from fixed pre-configured values to dynamic values calculated in real-time based on vehicle position, speed, and photogrammetric requirements. This parameter adaptation ensures precise image coverage without requiring complex manual setup, as the system automatically adjusts parameters during operation.
3Manufacturing precision
If the UAV holds position before each image capture, then high quality images are obtained, but the surveying time increases significantly
Solution Approach 1:
The system performs preliminary calculations of optimal trigger times before image capture based on predicted vehicle position and velocity. By pre-calculating when to trigger each camera based on forward telemetry data, the system ensures high-quality images are captured at the right moment without requiring the UAV to pause or hold position.
Solution Approach 2:
The system maintains continuous vehicle motion throughout the survey by eliminating pause-and-capture cycles. Multiple cameras enable continuous image acquisition at different positions along the flight path, maintaining the useful action of data collection without interruption while preserving image quality through precise triggering timing.
4Productivity
If multiple cameras are used with real-time triggering, then survey speed increases, but the system complexity increases
Solution Approach 1:
The system uses a single processor to perform multiple functions: controlling multiple cameras, processing telemetry data, calculating trigger times, and managing image acquisition. This multi-functionality allows the system to achieve high survey speed with multiple cameras while minimizing the increase in complexity by consolidating control functions in one unit.
Data Source
AI summary
A photogrammetry system includes a memory, a processor, and a geo-positioning device. The geo-positioning device outputs telemetry regarding a vehicle on which one or more cameras are mounted. The processor can receive first telemetry from the geo-positioning device characterizing the vehicle telemetry at a first time, camera specification(s) regarding the cameras, photogrammetric requirement(s) for captured images, and a last camera trigger time. The processor can determine a next trigger time for the cameras based upon the received telemetry, camera specification(s), photogrammetric requirement(s), and last trigger time. The processor can transmit a trigger signal to the camera(s) and the geo-positioning device to cause the camera(s) to acquire images of a target and the geo-positioning device to store second vehicle telemetry data characterizing the vehicle telemetry at a second time that is after the first time and during acquisition of the images. The processor can receive the acquired images from the cameras.