Details
| Original language | English |
|---|---|
| Title of host publication | Electro-Optical Remote Sensing XVI |
| Editors | Gary W. Kamerman, Ove Steinvall |
| Publisher | SPIE |
| ISBN (electronic) | 9781510655478 |
| Publication status | Published - 2 Nov 2022 |
Publication series
| Name | Proceedings of SPIE - The International Society for Optical Engineering |
|---|---|
| Volume | 12272 |
| ISSN (Print) | 0277-786X |
| ISSN (electronic) | 1996-756X |
Abstract
In search and rescue (SAR) missions every minute counts. Semi-collapsed buildings are among the difficult scenarios encountered by search and rescue teams. An UAV-based exploration system can provide crucial information on the accessibility of different sectors, hazards, and injured people. The research project “UAV-Rescue” aims to provide UAV-borne sensing and investigate the use of AI to support this powerful tool. The sensor suite contains a radar sensor for detecting people based on breath and pulse movement. A neural network interprets the extracted data to identify signs of human life and as such persons that need rescuing. We also fuse radar and lidar data to explore the environment of the UAV and obtain a robust basis for simultaneous localization and mapping even under restricted visibility conditions. Additionally, we plan to use AI to support the path planning of the drone taking the digital map as input. Furthermore, AI is leveraged to map intact and damaged building structures. Potentially hazardous gases common to urban settings are tracked. We fuse the acquired information into a model of the explored area with marked locations of potential hazards and people to be rescued. The project also addresses ethical and societal issues raised by the use of UAVs close to people as well as AI supported decision making. The talk will present the system concept including interfaces and sensor fusion approaches. We will show first results of a research project from static and dynamic measurement campaigns demonstrating the capability of radar and lidar based sensing in a complex urban environment.
Keywords
- Radar, Unmanned aerial vehicles, Sensors, LIDAR, Artificial intelligence, Buildings, Legal, search and rescue, vital signs, DNN, AI, UAV, radar, lidar, 3D mapping
ASJC Scopus subject areas
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
- Physics and Astronomy(all)
- Condensed Matter Physics
- Mathematics(all)
- Applied Mathematics
- Engineering(all)
- Electrical and Electronic Engineering
- Computer Science(all)
- Computer Science Applications
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- BibTeX
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Electro-Optical Remote Sensing XVI. ed. / Gary W. Kamerman; Ove Steinvall. SPIE, 2022. 1227203 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 12272).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - UAV-borne remote sensing for AI-assisted support of search and rescue missions
AU - Herschel, Reinhold
AU - Wallrath, Patrick
AU - Hofstätter, Michael
AU - Taupe, Philipp
AU - Krüger, Emily
AU - Philippi, Martina
AU - Kunze, Julian
AU - Rotter, Jan Michel
AU - Heusinger, Victoria
AU - Ari, Meral
AU - Kastner, René
AU - Al-Akrawi, Astrid
N1 - Funding Information: We want to thank the German Ministry Federal for Education and Research for funding the German part of UAV-Rescue within the federal government framework program Research for Civil Security. The Austrian part of UAV-Rescue is funded by the Austrian security research program KIRAS of the Federal Ministry of Agriculture, Regions and Tourism.
PY - 2022/11/2
Y1 - 2022/11/2
N2 - In search and rescue (SAR) missions every minute counts. Semi-collapsed buildings are among the difficult scenarios encountered by search and rescue teams. An UAV-based exploration system can provide crucial information on the accessibility of different sectors, hazards, and injured people. The research project “UAV-Rescue” aims to provide UAV-borne sensing and investigate the use of AI to support this powerful tool. The sensor suite contains a radar sensor for detecting people based on breath and pulse movement. A neural network interprets the extracted data to identify signs of human life and as such persons that need rescuing. We also fuse radar and lidar data to explore the environment of the UAV and obtain a robust basis for simultaneous localization and mapping even under restricted visibility conditions. Additionally, we plan to use AI to support the path planning of the drone taking the digital map as input. Furthermore, AI is leveraged to map intact and damaged building structures. Potentially hazardous gases common to urban settings are tracked. We fuse the acquired information into a model of the explored area with marked locations of potential hazards and people to be rescued. The project also addresses ethical and societal issues raised by the use of UAVs close to people as well as AI supported decision making. The talk will present the system concept including interfaces and sensor fusion approaches. We will show first results of a research project from static and dynamic measurement campaigns demonstrating the capability of radar and lidar based sensing in a complex urban environment.
AB - In search and rescue (SAR) missions every minute counts. Semi-collapsed buildings are among the difficult scenarios encountered by search and rescue teams. An UAV-based exploration system can provide crucial information on the accessibility of different sectors, hazards, and injured people. The research project “UAV-Rescue” aims to provide UAV-borne sensing and investigate the use of AI to support this powerful tool. The sensor suite contains a radar sensor for detecting people based on breath and pulse movement. A neural network interprets the extracted data to identify signs of human life and as such persons that need rescuing. We also fuse radar and lidar data to explore the environment of the UAV and obtain a robust basis for simultaneous localization and mapping even under restricted visibility conditions. Additionally, we plan to use AI to support the path planning of the drone taking the digital map as input. Furthermore, AI is leveraged to map intact and damaged building structures. Potentially hazardous gases common to urban settings are tracked. We fuse the acquired information into a model of the explored area with marked locations of potential hazards and people to be rescued. The project also addresses ethical and societal issues raised by the use of UAVs close to people as well as AI supported decision making. The talk will present the system concept including interfaces and sensor fusion approaches. We will show first results of a research project from static and dynamic measurement campaigns demonstrating the capability of radar and lidar based sensing in a complex urban environment.
KW - Radar
KW - Unmanned aerial vehicles
KW - Sensors
KW - LIDAR
KW - Artificial intelligence
KW - Buildings
KW - Legal
KW - search and rescue
KW - vital signs
KW - DNN
KW - AI
KW - UAV
KW - radar
KW - lidar
KW - 3D mapping
UR - http://www.scopus.com/inward/record.url?scp=85145436526&partnerID=8YFLogxK
U2 - 10.1117/12.2636032
DO - 10.1117/12.2636032
M3 - Conference contribution
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Electro-Optical Remote Sensing XVI
A2 - Kamerman, Gary W.
A2 - Steinvall, Ove
PB - SPIE
ER -