TRIFFID

Acronym: TRIFFID
Title: auTonomous Robotic aId For increasing FIrst responDers efficiency 

What is TRIFFID about?
TRIFFID aims to maximize the efficiency of ‘First Responders’ (FRs) in field operations, by expanding remote and smart robotic scouting in disaster sites. Most disaster-related deaths are in urban areas. Urban areas often bear the impact of disaster damages and losses due to their dense population, infrastructure, business presence and cultural heritage. ¾ of the European population currently resides in cities, towns and suburbs.
 

So how will TRIFFID be a ‘Change Maker’ ?
TRIFFID will build a system and demonstrate its real-world effectiveness for ‘First Responders’ (FRs)  facing fire, earthquake, and flood scenarios. For example: Satellite Imagery (e.g., from Copernicus) is commonly employed for providing an initial picture of the evolving disaster to the First Responders (FRs) and Civil Protection (CP) authorities. Automated analysis using computer vision is typically done by using either traditional image processing or machine learning. The goal is to geolocate burnt zones, fire frontiers, flooded areas, etc. and provide this information to the FR/CP authorities.  Yet, the accuracy of existing methods is not always high, due to the scarcity of relevant large-scale training datasets. As such, ‘Autonomous Mobile Robots' will complement and facilitate human effort, reduce the exposure of their personnel to dangers and provide them with credible information as soon as possible from the disaster scene.

What is the advantage of robots?
The main advantages of robots are their endurance and their expendability. However, to ensure that humans control the complete range of these advantages, a significant level of cognitive autonomy/artificial intelligence (AI) is required in the deployed robots.  

The use of teleoperated or semi-autonomous robots protects human FRs from hazards, accelerates response times and facilitates enhanced situational awareness, thanks to the deployment and fusion of multiple on-robot sensors, but still does not lessen the burden of manual robot supervision.  

At present, the cognitive autonomy is restricted and during on-scene operations places significant limits on achievable FR efficiency gains. With the TRIFFID project, the consortium aims to boost the efficiency and safety of FRs field operations by facilitating the adoption of effective autonomous disaster robotics solutions. TRIFFID intends to develop a unified system that integrates optimally into FRs operational procedures.

Why is TRIFFID important?
The VUB will be taking the lead in defining and monitoring the legal (incl. privacy and security) and ethical (incl. sex/gender/intersectional, non-discrimination, human agency, human dignity) aspects of the project, dual-use issues (potential project technology misuse to inflict harm), and any relevant issues arising from the involvement of humans at any stage, from HRI or robot navigation near humans. A legal analysis will be performed to identify relevant national and European legislation (e.g., GDPR, AI Act, etc.). The focus will be placed on relevant AI ethics guidelines, including the HLEG’s1 Ethics Guidelines for Trustworthy AI.