Environment Mapping and Urgent Landing Planning for Low-Altitude UAS Operations
Small Unmanned Aircraft Systems (sUAS) are expected to proliferate in low-altitude airspace and will require flight near buildings and over people. Robust urgent landing capabilities including landing site selection are critical for safety. However, conventional fixed-wing emergency landing sites such as open fields and empty roadways are rare in and around cities. Our work uniquely considers a city's many unoccupied flat rooftops as possible nearby landing sites. We propose novel methods to identify flat rooftop buildings, isolate their flat surfaces, and find touchdown points that maximize distance to obstacles. We model flat rooftop surfaces as polygons that capture their boundaries and obstructions. We process satellite images, airborne LiDAR point clouds, and map building outlines to generate rooftop maps with a multi-stage machine learning pipeline. We propose a computational geometry method (Polylidar3D) that reliably extracts flat rooftop surfaces from archived data sources. We model risk as an innovative combination of landing site and path risk metrics and conduct a multi-objective Pareto front analysis for sUAS urgent landing in cities. A high-fidelity simulated city is constructed in the Unreal game engine with a statistically-accurate representation of rooftop obstacles. Fusion of Polylidar3D and RGBD semantic segmentation output shows improved intersection-over-union (IOU) accuracy in landing site identification compared to using LiDAR data only.
1PDH will be awarded to the attendees
Date and Time
Location
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Registration
- Date: 22 Sep 2022
- Time: 05:30 PM to 06:30 PM
- All times are (GMT-06:00) US/Central
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- Lincoln, Nebraska
- United States 68588
- Starts 29 March 2022 12:00 AM
- Ends 22 September 2022 05:30 PM
- All times are (GMT-06:00) US/Central
- No Admission Charge
Speakers
Ella Atkins
Biography:
Dr. Ella Atkins is a Professor in the University of Michigan’s Aerospace Engineering and Robotics Departments. Dr. Atkins holds B.S. and M.S. degrees in Aeronautics and Astronautics from MIT and M.S. and Ph.D. degrees in Computer Science and Engineering from the University of Michigan. She is an AIAA Fellow and private pilot. She served on the National Academy’s Aeronautics and Space Engineering Board and has authored over 200 refereed journal and conference papers. Dr. Atkins has pursued research in AI-enabled autonomy and control to support resilience and contingency management in manned and unmanned Aerospace applications. She is currently Editor-in-Chief of the AIAA Journal of Aerospace Information Systems (JAIS).