Aircraft Landing Zone Imaging for 3D Obstacle Evaluation
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Solution Overview
Problem
Conventional methods for landing zone evaluation fail to effectively detect and avoid obstacles in real-time, posing risks to aircraft safety and passenger safety.
Innovation Solution
A method and apparatus that utilize imaging sensors and navigation data to capture and process images of a landing zone, generating a point cloud, filtering outliers, and localizing the data into world coordinates to create a surface model, enabling navigation instructions to avoid obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used for landing zone evaluation, then the system is simple, but obstacle detection precision and safety are insufficient
Solution Approach 1:
The landing zone evaluation system segments the detection process into multiple independent modules: image capture module, point cloud generation module, obstacle detection module, and safety evaluation module. Each module performs a specific function, allowing the system to achieve high detection precision through specialized processing while managing complexity through modular architecture.
Solution Approach 2:
The system transitions from conventional two-dimensional image analysis to three-dimensional point cloud processing. By capturing depth information and converting images into 3D spatial representations, the system achieves superior obstacle detection precision and can identify objects that would be invisible or ambiguous in 2D images alone.
2Reliability
If real-time obstacle detection is implemented, then aircraft safety is improved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary processing by generating point clouds from captured images in real-time as the aircraft approaches the landing zone. This preliminary 3D reconstruction enables subsequent obstacle detection to be performed rapidly on already-processed spatial data, reducing the time required for final safety evaluation while maintaining high reliability.
Solution Approach 2:
The system replaces conventional mechanical or manual landing zone assessment methods with automated optical sensing and computational processing. Imaging sensors and point cloud algorithms automatically detect obstacles and evaluate safety, eliminating the need for time-consuming manual inspection while providing continuous real-time monitoring for enhanced aircraft safety.
3Measurement precision
If detailed point cloud processing is performed, then obstacle localization accuracy is improved, but computational complexity increases
Solution Approach 1:
The system extracts only the essential features from the complete point cloud data for obstacle localization. Instead of processing every single point in the detailed point cloud, the algorithm identifies and extracts key characteristic points that define obstacle positions, shapes, and critical dimensions. This extraction approach maintains high localization accuracy while significantly reducing computational complexity.
Solution Approach 2:
The system applies different processing quality levels to different regions of the landing zone based on their importance. Areas closer to the aircraft trajectory or containing potential obstacles receive higher processing detail and more rigorous analysis, while distant or clear areas use simplified processing. This local quality adjustment optimizes the balance between localization accuracy and computational complexity.
Data Source
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AI summary
Disclosed herein is a system that comprises one or more imaging sensors coupled to an aircraft and one or more navigation sensors coupled to the aircraft proximate to the one or more imaging sensors. The system further comprises an imaging module configured to capture images of a landing zone for the aircraft while the aircraft is in flight. The system additionally comprises a location determining module configured to associate a corresponding one of a plurality of location data with each one of the captured images. The plurality of location data is determined using one or more navigation sensors coupled to the aircraft. The system also comprises an object-identifying module configured to identify and locate one or more objects within the landing zone, relative to the aircraft, using the captured images and the location data associated with the captured images.