group
What campus are you from?
Daytona Beach
Authors' Class Standing
Rachel Jacobsen Liam Abraham Nikolaos Triantafilloy
Lead Presenter's Name
Ethan Thomas
Faculty Mentor Name
Monica Garcia
Abstract
Man-overboard (MOB) events continue to pose a significant challenge to maritime safety, where rapid and reliable detection of a person in the water is critical to survival. Traditional search and rescue (SAR) operations rely on manual surveillance from ships or crewed aircraft. These operations can be slow to initiate, manpower-intensive, and limited by poor visibility, sea state, and weather. Autonomous systems, particularly uncrewed aerial systems (UAS), have the potential to drastically improve the effectiveness of SAR operations. Our team will investigate the use of a UAS to improve the support of SAR operations with a focus on developing an advanced object detection system to autonomously identify a person in the water across a variety of environmental conditions. To achieve this objective, the team will research, integrate, and test imaging sensors optimized for maritime detection. In addition, an open-source software architecture leveraging Robot Operating System 2 (ROS2) middleware will be developed to enable modular autonomy through custom nodes and packages dedicated to perception, processing, and communication. The system will undergo rigorous testing and evaluation in both controlled and operationally representative maritime environments. The results of this will provide a solid foundation for future development of the UAS in future project stages.
Did this research project receive funding support from the Office of Undergraduate Research.
No
MOB-air: MOB Detection from a UAV
Man-overboard (MOB) events continue to pose a significant challenge to maritime safety, where rapid and reliable detection of a person in the water is critical to survival. Traditional search and rescue (SAR) operations rely on manual surveillance from ships or crewed aircraft. These operations can be slow to initiate, manpower-intensive, and limited by poor visibility, sea state, and weather. Autonomous systems, particularly uncrewed aerial systems (UAS), have the potential to drastically improve the effectiveness of SAR operations. Our team will investigate the use of a UAS to improve the support of SAR operations with a focus on developing an advanced object detection system to autonomously identify a person in the water across a variety of environmental conditions. To achieve this objective, the team will research, integrate, and test imaging sensors optimized for maritime detection. In addition, an open-source software architecture leveraging Robot Operating System 2 (ROS2) middleware will be developed to enable modular autonomy through custom nodes and packages dedicated to perception, processing, and communication. The system will undergo rigorous testing and evaluation in both controlled and operationally representative maritime environments. The results of this will provide a solid foundation for future development of the UAS in future project stages.