AutoSOS: Towards Multi-UAV Systems Supporting Maritime Search and Rescue with Lightweight AI and Edge Computing

TL;DR

AutoSOS introduces a multi-UAV rescue platform utilizing lightweight AI and edge computing for efficient maritime search and rescue, enabling autonomous reconnaissance, sensor fusion, and adaptive communication in challenging environments.

Contribution

The paper presents a novel autonomous multi-robot system with lightweight AI models for sensor fusion and object detection, optimized for embedded devices in maritime rescue scenarios.

Findings

Effective sensor fusion on embedded devices.

Autonomous reconfiguration for multi-hop communication.

Enhanced initial assessment accuracy.

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.