LIDAR Landing Zone Detection Using Marking Verification
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Solution Overview
Problem
Current autonomous landing zone detection systems are limited in identifying appropriate landing zones, often choosing inappropriate locations due to their inability to distinguish between different areas, leading to safety concerns during landing operations, especially in low visibility conditions.
Innovation Solution
A sensor system utilizing LIDAR technology to scan areas, filter point cloud data based on intensity, and apply template matching algorithms to identify specific markings such as runway numbers and patterns, allowing for precise verification of landing zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional autonomous landing zone detection systems are used, then the system can detect potential landing zones, but the system may choose inappropriate locations such as active taxiways or grass patches
Solution Approach 1:
The system segments the landing zone detection task into multiple components: LIDAR point cloud processing, marking detection, pattern recognition, and verification against predefined criteria. This segmentation allows each component to be optimized independently, improving overall detection accuracy and reliability.
Solution Approach 2:
The patent introduces an intermediary verification layer that checks detected landing zones against multiple criteria including marking patterns, geometric properties, and environmental factors. This intermediary step acts as a mediator between raw detection data and final landing zone selection, preventing inappropriate locations from being chosen.
2Measurement precision
If the system scans and analyzes detailed area data to identify markings, then landing zone identification accuracy improves, but the processing time and computational complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-processing LIDAR point cloud data to filter and segment relevant features before detailed marking identification. Predefined marking templates and patterns are prepared in advance, allowing for faster matching during the actual detection process.
Solution Approach 2:
The patent replaces traditional mechanical scanning and analysis methods with optical LIDAR technology and automated image processing algorithms. This substitution enables rapid data acquisition and processing, reducing the time required for detailed marking identification while maintaining high accuracy.
3Measurement precision
If the system uses LIDAR to obtain detailed point cloud data with intensity information, then the precision of area analysis improves, but the data processing complexity and energy consumption increase
Solution Approach 1:
The system extracts only the essential intensity information from LIDAR point cloud data that is relevant for marking detection and landing zone identification. By filtering and selecting only the necessary data features, the system reduces processing complexity while maintaining the precision benefits of detailed scanning.
Solution Approach 2:
The patent changes the parameter representation of LIDAR data by converting raw point cloud information into processed features such as intensity histograms, edge detections, and marking patterns. This parameter transformation simplifies the data structure while preserving the precision needed for accurate area analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and safe identification of landing zones, reducing the risk of landing on inappropriate locations and enhancing operational safety by providing real-time, precise guidance for aircraft.
Implementation Method 1
using a LIDAR system configured to emit an optical beam to obtain point cloud data of the area based on a returned portion of the optical beam
Implementation Method 2
obtain point cloud data of the area based on a returned portion of the optical beam
Data Source
AI summary
A method of detecting a landing zone includes scanning an area using a sensor system to obtain data of the area. One or more markings are identified from the data. The one or more markings are verified as corresponding to an intended landing zone.