TRIFFID - auTonomous Robotic aId For increasing FIrst responDers efficiency

 TRIFFID targets the development of an integrated approach for maximizing the efficiency of First Responders (FR) field operations, by advancing remote and smart robotic reconnaissance in disaster sites, while integrating it into European Civil Protection procedures. The project will deliver the following advancements:- Hybrid legged UGV+UAV robotic platform for autonomous real-time reconnaissance in dynamic environments. The TRIFFID robots will receive orders in the field by a human FR crew. Yet, the platform will feature an impressive level of low-level cognitive autonomy, thanks to advanced AI and Deep Neural Networks (DNNs), thus minimizing human supervision: the FR crew will be free to handle high-level decisions and define response strategy, without having to worry about controlling the robots, mapping the disaster site or advancing themselves into unknown/potentially dangerous territory. Still, the human FRs will be able to switch the robots to remotely guided operation on-demand. - Central Ground-Station with an advanced Augmented Reality (AR) interface, managed by a human Operator. The TRIFFID Ground-Station will merge and display all collected information in near-real-time, providing the remote Operator with a clearer, fuller and more accurate semantic map of the disaster site. - Analysis of technological, operational, organizational and policy aspects in the context of the overall FR ecosystem. The design of the TRIFFID system and the specification of its exact capabilities will proceed by considering the current technological landscape, as well as the entire operational environment and organizational structure of FRs, so that effective disaster robotics solutions are gracefully integrated into CP infrastructure. - FR training activities: The project will exploit different pathways for implementing and boosting the adoption of the TRIFFID system by FR personnel in their everyday activities, including the development of detailed training curricula, the organization of training exercises, knowledge transfer and skill acquisition activities, etc. - SSH, robot acceptance and industrial engagement: The design and evaluation of TRIFFID will consider in-depth all relevant legal, ethical, societal and usability issues, targeting maximal adoption by FRs in their daily operations, a high level of trust to the robotic platform and an engagement of European tech industry with CP.