Drone Landing Pad Detection for Autonomous Precision Landing
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Solution Overview
Problem
Conventional drone systems require extensive operator training and are prone to errors during remote landing, especially in challenging environments, leading to increased costs and risk of drone damage.
Innovation Solution
A computer-implemented method and system for automatically landing a drone on a landing pad with guiding elements, using image processing to compute a segmentation mask, extract guiding elements, and navigate the drone to the central region of the pad, enabling autonomous landing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If remote control landing is used, then operator control is maintained, but operator training time and error risk increase
Solution Approach 1:
The drone performs landing autonomously by detecting and navigating to the landing pad itself, without requiring external operator control. The system uses onboard cameras and image processing to automatically identify the pad, compute its location, and guide the drone to the correct position, eliminating the need for operator training while maintaining safe landing operations
Solution Approach 2:
The manual remote control system is replaced with an automated computer vision and image processing system. The drone's onboard computer captures images, processes them to identify landing pad features, and automatically computes navigation commands, substituting the mechanical remote control interface with an automated digital system that eliminates operator training requirements
2Ease of operation
If remote control landing is used, then operator control is maintained, but drone damage risk increases
Solution Approach 1:
The drone autonomously performs the landing function by detecting the landing pad and navigating to it without operator intervention. This self-service capability eliminates human error in critical landing phases, reducing the risk of drone damage while maintaining operational reliability
Solution Approach 2:
The system continuously captures images during approach, processes them to detect landing pad features, and uses this feedback to adjust the drone's position in real-time. This closed-loop feedback system ensures accurate positioning and reduces the risk of damage by automatically correcting for deviations from the target location
3Measurement precision
If automated landing with image processing is used, then landing precision is improved, but computational complexity increases
Solution Approach 1:
The image processing is divided into distinct computational stages: initial feature detection to identify the landing pad region, followed by detailed analysis of guiding elements within that region, and finally computation of the central location. This segmentation of the computational process reduces overall complexity by breaking down the complex task into manageable, sequential steps
Solution Approach 2:
The system performs preliminary image processing to detect and segment the landing pad region before conducting detailed analysis of guiding elements. This preliminary action reduces the computational burden of subsequent processing by limiting detailed analysis to only the relevant region of interest, thereby improving precision without proportionally increasing overall computational complexity
Data Source
AI summary
There is provided a method of automatically landing a drone on a landing pad having thereon guiding-elements arranged in a pattern relative to a central region of the landing pad, comprising: receiving first image(s) captured by a camera of the drone, processing the first image(s) to compute a segmentation mask according to an estimate of a location of the landing pad, receiving second image(s) captured by the camera, processing the second image(s) according to the segmentation mask to compute a segmented region and extracting from the segmented region guiding-element(s), determining a vector for each of the extracted guiding-element(s), and aggregating the vectors to compute an estimated location of the central region of the landing pad, and navigating and landing the drone on the landing pad according to the estimated location of the central region of the landing pad.