Abstract
The integration of unmanned aerial vehicles (UAV s) into commercial and military applications marks a significant advancement in aerial technology, requiring robust systems for safe operation. Among the numerous challenges, the selection of safe landing sites in emergencies remains a critical concern. This paper contributes to this emerging field by developing an autonomous safe landing system designed to improve the operational safety of UAV s in diverse environments. Our method uses a shifted grid technique for point cloud evaluation to identify safe landing sites based on terrain features such as slope, roughness, and peak distance differences. We validated our approach through extensive flight tests using a custom drone equipped with a LIDAR sensor. The UAV performed a safe landing on unstructured, unknown, and uncooperative terrain with real-time on-board computation. The results show the ability of the algorithm to improve UAV safety and operational reliability in various challenging conditions.
Original language | English |
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Title of host publication | DASC 2024 - Digital Avionics Systems Conference, Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9798350349610 |
DOIs | |
Publication status | Published - 2024 |
Externally published | Yes |
Event | 43rd AIAA DATC/IEEE Digital Avionics Systems Conference, DASC 2024 - San Diego, United States Duration: 29 Sept 2024 → 3 Oct 2024 |
Publication series
Name | AIAA/IEEE Digital Avionics Systems Conference - Proceedings |
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ISSN (Print) | 2155-7195 |
ISSN (Electronic) | 2155-7209 |
Conference
Conference | 43rd AIAA DATC/IEEE Digital Avionics Systems Conference, DASC 2024 |
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Country/Territory | United States |
City | San Diego |
Period | 29/09/24 → 3/10/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- autonomous
- drone
- emergency
- landing
- UAV
- unknown terrain