Drone Altitude Control for Spatial Resolution and Battery Tradeoffs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current drones face a tradeoff between autonomy and image quality when capturing aerial images, as high altitudes provide broader coverage but lower resolution, while low altitudes require more images and may deplete battery quickly, making it challenging for real-time processing by computer vision algorithms.
Innovation Solution
A method and system that control the drone's altitude based on confidence scores from computer vision algorithms, adjusting the flight altitude to recapture images if the confidence score is below a threshold, optimizing image quality and autonomy by using spatial patterns and efficient image processing to ensure real-time execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the drone flies at high altitude to capture the entire region, then the coverage area is improved, but the spatial resolution deteriorates
Solution Approach 1:
The drone dynamically adjusts its flight altitude based on confidence scores from computer vision algorithms. When confidence is low, the drone automatically lowers altitude to capture higher resolution images, and when confidence is high, it maintains higher altitude for broader coverage. This dynamic adaptation resolves the contradiction between coverage area and spatial resolution.
2Measurement precision
If the drone flies at low altitude to capture detailed images, then the spatial resolution is improved, but the battery consumption increases
Solution Approach 1:
The system implements feedback control by processing captured images through computer vision algorithms and using the confidence scores to determine subsequent flight altitude. This closed-loop feedback ensures the drone only lowers altitude when necessary (when confidence is low), optimizing the balance between spatial resolution and battery consumption.
Solution Approach 2:
The drone changes its operational parameters (flight altitude) based on real-time assessment of image quality requirements. By adjusting altitude as a variable parameter response to confidence scores, the system optimizes energy usage while maintaining necessary image quality for the mapping task.
3Measurement precision
If the drone captures more images at low altitude to ensure quality, then the image quality is improved, but the autonomy time deteriorates
Solution Approach 1:
The system applies partial action by capturing high-resolution images only in regions where confidence scores indicate insufficient detection quality. Rather than uniformly capturing all regions at high resolution, the drone selectively processes areas needing improvement, thereby extending autonomy time while maintaining necessary image quality.
4Measurement precision
If the drone recaptures images with low confidence scores, then the detection accuracy is improved, but the time consumption increases
Solution Approach 1:
The system performs preliminary assessment of image quality through computer vision algorithms during the initial capture phase. By identifying low-confidence regions upfront, the drone can plan efficient recapture routes and prioritize areas needing re-imaging, reducing overall time consumption while improving detection accuracy in critical areas.
Data Source
AI summary
An image of a region captured by an unmanned aerial vehicle flying at an altitude may be received. A computer vision algorithm may be executed with the image as an input to compute an overall confidence score associated with detecting one or more candidate objects in the image. Responsive to determining that the confidence score is below a predefined minimum threshold or above a predefined maximum threshold, the unmanned aerial vehicle may be controlled to change its altitude and recapture the image of the region at a new position. Responsive to determining that the overall confidence score is not below the predefined minimum threshold, information associated with the image may be stored on a storage device.