Real-Time Safe Landing Zone Identification Based on Airborne LiDAR

Area of Science:

• Robotics and Automation
• Aerospace Engineering
• Geospatial Science

Background:

• Real-time Digital Surface Model (DSM) generation is crucial for aircraft landing in degraded visual environments.
• Existing airborne laser scanning (ALS) filtering algorithms are computationally expensive and slow, hindering real-time applications.
• Safe landing zone (SLZ) identification is vital to prevent accidents caused by poor visibility and obstacles.

Purpose of the Study:

• To design and implement an efficient real-time algorithm for SLZ identification on limited-resource embedded processors.
• To process 3D LiDAR point cloud data for safe aircraft/helicopter landings.
• To overcome the limitations of computationally expensive and time-consuming existing algorithms.

Main Methods:

• Developed a novel, efficient algorithm for real-time processing of 3D LiDAR point cloud data.
• Implemented the algorithm in C++ for deployment on embedded systems.
• Validated the algorithm's performance using professional flight simulation software.

Main Results:

• The algorithm successfully identified the best safe landing zone (SLZ) in real-time.
• Demonstrated the algorithm's effectiveness in assisting pilots during simulated landings.
• Validated the accuracy of the developed method by comparing results with existing maps.

Conclusions:

• The developed algorithm provides an efficient, real-time solution for SLZ identification using LiDAR data.
• This technology can significantly enhance aircraft safety, especially in degraded visual environments.
• The method is suitable for deployment on embedded processors, enabling real-time assistance for pilots.