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TRIFFID: Autonomous Robotic Aid For Increasing First Responders Efficiency

Authors :
Cani, Jorgen
Koletsis, Panagiotis
Foteinos, Konstantinos
Kefaloukos, Ioannis
Argyriou, Lampros
Falelakis, Manolis
Del Pino, Iván
Santamaria-Navarro, Angel
Čech, Martin
Severa, Ondřej
Umbrico, Alessandro
Fracasso, Francesca
Orlandini, AndreA
Drakoulis, Dimitrios
Markakis, Evangelos
Papadopoulos, Georgios Th.
Publication Year :
2025

Abstract

The increasing complexity of natural disaster incidents demands innovative technological solutions to support first responders in their efforts. This paper introduces the TRIFFID system, a comprehensive technical framework that integrates unmanned ground and aerial vehicles with advanced artificial intelligence functionalities to enhance disaster response capabilities across wildfires, urban floods, and post-earthquake search and rescue missions. By leveraging state-of-the-art autonomous navigation, semantic perception, and human-robot interaction technologies, TRIFFID provides a sophisticated system com- posed of the following key components: hybrid robotic platform, centralized ground station, custom communication infrastructure, and smartphone application. The defined research and development activities demonstrate how deep neural networks, knowledge graphs, and multimodal information fusion can enable robots to autonomously navigate and analyze disaster environ- ments, reducing personnel risks and accelerating response times. The proposed system enhances emergency response teams by providing advanced mission planning, safety monitoring, and adaptive task execution capabilities. Moreover, it ensures real- time situational awareness and operational support in complex and risky situations, facilitating rapid and precise information collection and coordinated actions.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2502.09379
Document Type :
Working Paper