UAV Landing Obstacle Detection Using 3D Image Reconstruction
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) face challenges in safely transitioning from horizontal to vertical flight modes, particularly in identifying obstacles in landing areas with small spatial extent or similar colors/textures to the surrounding environment, which can lead to hazards during landing operations.
Innovation Solution
The system captures multiple images of the landing area using onboard cameras, processes them to determine pixel disparities using optical flow or stereo matching algorithms, generating a 3D reconstruction and difference images to detect obstacles, allowing the UAV to abort or modify the landing operation if obstacles are present.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual imaging data is used to identify obstacles in landing areas, then obstacles with distinct colors or textures can be readily identified, but obstacles with small spatial extent or similar colors/textures to the landing area cannot be reliably detected
Solution Approach 1:
The patent transitions from 2D visual imaging data to 3D spatial representation by capturing images at multiple altitudes and constructing a three-dimensional model of the landing area. This dimensional transformation enables the detection of obstacles with small spatial extent or similar appearance to the landing area, as their spatial position and height become distinguishable in the 3D model even when they are indistinguishable in 2D images.
Solution Approach 2:
The system performs preliminary obstacle detection by capturing images at a first altitude before final landing, constructs a 3D model, and identifies obstacles in advance. This preliminary action allows the UAV to assess landing safety and abort or modify the landing operation before committing to the final descent, preventing potential collisions with undetected obstacles.
2Reliability
If the UAV descends to a designated landing area, then it can perform precise landing operations, but it risks colliding with undetected obstacles that pose substantial hazards
Solution Approach 1:
The system performs preliminary obstacle detection and landing area assessment by capturing images at a first altitude, constructing a 3D model, and identifying obstacles before the final landing descent. This preliminary action enables the UAV to abort or modify the landing operation if obstacles are detected, ensuring safe landing operations by eliminating collision risks from undetected obstacles.
Solution Approach 2:
The system uses imaging devices to capture images of the landing area, processes these images to generate 3D models, and uses this feedback information to determine whether to proceed with or abort the landing operation. The feedback loop continues during descent with images captured at multiple altitudes, allowing real-time assessment and adjustment of the landing decision based on detected obstacles.
3Reliability
If multiple images are captured and processed to generate 3D reconstruction and difference images, then obstacle detection reliability is improved, but system complexity and processing time increase
Solution Approach 1:
The image processing is segmented into distinct stages: capturing images at multiple altitudes, generating 3D models from these images, constructing difference images by comparing 3D models, and finally determining obstacle presence. This segmentation allows the complex processing task to be divided into manageable steps, each with a specific function, reducing overall system complexity while maintaining high detection reliability.
Data Source
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AI summary
Aerial vehicles that are equipped with one or more imaging devices may detect obstacles that are small in size, or obstacles that feature colors or textures that are consistent with colors or textures of a landing area, using pairs of images captured by the imaging devices. Disparities between pixels corresponding to points of the landing area that appear within each of a pair of the images may be determined and used to generate a reconstruction of the landing area and a difference image. If either the reconstruction or the difference image indicates the presence of one or more obstacles, a landing operation at the landing area may be aborted or an alternate landing area for the aerial vehicle may be identified accordingly.