AutoSOS: Towards Multi-UAV Systems Supporting Maritime Search and Rescue with Lightweight AI and Edge Computing
May 07, 2020 Β· Declared Dead Β· π arXiv.org
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Authors
Jorge PeΓ±a Queralta, Jenni Raitoharju, Tuan Nguyen Gia, Nikolaos Passalis, Tomi Westerlund
arXiv ID
2005.03409
Category
cs.RO: Robotics
Cross-listed
cs.LG
Citations
32
Venue
arXiv.org
Last Checked
6 months ago
Abstract
Rescue vessels are the main actors in maritime safety and rescue operations. At the same time, aerial drones bring a significant advantage into this scenario. This paper presents the research directions of the AutoSOS project, where we work in the development of an autonomous multi-robot search and rescue assistance platform capable of sensor fusion and object detection in embedded devices using novel lightweight AI models. The platform is meant to perform reconnaissance missions for initial assessment of the environment using novel adaptive deep learning algorithms that efficiently use the available sensors and computational resources on drones and rescue vessel. When drones find potential objects, they will send their sensor data to the vessel to verity the findings with increased accuracy. The actual rescue and treatment operation are left as the responsibility of the rescue personnel. The drones will autonomously reconfigure their spatial distribution to enable multi-hop communication, when a direct connection between a drone transmitting information and the vessel is unavailable.
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