Drone Shelf Label Imaging With Two-Stage Flight Path Planning
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Solution Overview
Problem
Current photographing devices for capturing shelf labels are not capable of efficiently flying and photographing labels from a closer distance, limiting their ability to accurately read information and optimize flight paths for energy conservation.
Innovation Solution
A photographing device equipped with a camera interface, flight control interface, and a processor that enables it to fly autonomously, extract object regions, set optimal flight paths, and acquire images from both a wide and close distance, allowing for efficient data transmission and reading of shelf label information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the photographing device flies closer to photograph shelf labels, then image quality and reading accuracy improve, but energy consumption increases
Solution Approach 1:
The device performs preliminary wide-area photographing from a higher altitude to identify shelf label positions and create a map, then uses this information to plan an optimized flight path that only approaches specific labels that need reading, avoiding unnecessary close-proximity flight and reducing overall energy consumption
Solution Approach 2:
The device uses image recognition to identify shelf labels and their positions, then feeds this information back to adjust the flight path dynamically, optimizing the balance between getting close enough for accurate reading and minimizing energy-consuming close-proximity flight time
2Loss of information
If the photographing device photographs the entire wide area first, then it can identify label positions, but it cannot capture labels in narrow areas from a close distance
Solution Approach 1:
The photographing process is segmented into two phases: first, wide-area photographing to identify all shelf label positions and create a comprehensive map; second, targeted close-proximity photographing of specific labels that require reading, using the previously acquired position information to guide the approach
Solution Approach 2:
The flight altitude and distance are made dynamic rather than fixed - the device adjusts its distance from the shelf based on the specific task: higher altitude for wide-area surveying, lower altitude for close-up label reading, optimizing both information acquisition and image quality as needed
Data Source
AI summary
A flying drone for shelf label checking includes a flying mechanism, a camera, and a camera interface configured to transmit and receive data to and from the camera. A flight control interface is configured to transmit and receive data to and from the flying mechanism. A processor is configured to acquire a first image of an object from a first distance with the camera, then extract an object region for the object from the first image. The processor then sets a flight path based on the object region and controls the flying mechanism to fly the camera along the flight path to a second distance that is closer to the object than the first distance. A second image of the object is then acquired from the second distance with the camera.