ATRACT: A Trustworthy Robotic Autonomous system to support Casualty Triage

Project Details

Description

Survival of a seriously injured battlefield casualty depends on the immediate actions after trauma. Where multiple casualties occur simultaneously, survival rates are optimised through effective, timely triage1 and – conventionally – through rapid casualty evacuation (CASEVAC) by Medical Emergency Response Team (MERT). Historically, about 40% of casualties died before reaching a medical aid post2. A total of 456 and 179 British military deaths in Afghanistan and Iraq cost the UK economy over £20.6 and £9.6 billion3, respectively. Recent proliferation and effectiveness of low-cost, accurate, shoulder-launched ground-to-air missiles has significantly disrupted helicopter operations in Ukraine4 and thus, presenting a heightened risk to CASEVAC operations.

The proposed ATRACT project will address this challenge in a novel way by designing, developing and field-testing a trustworthy drone-driven robotic autonomous system (RAS) to help a frontline medic – with limited ability to move between casualties – triage multiple battlefield casualties and support decision-making in the first ‘platinum ten minutes’ following trauma. ATRACT adopts an interdisciplinary and transformative research approach focusing on 1) accurate search and localisation of injured soldiers using advanced manoeuvring of a drone in difficult terrains, 2) a novel platform that combines advanced multimodal sensing, beyond state-of-the-art (SotA) object/event recognition methods targeting frontline soldiers, 3) real-time monitoring of their injury severity and vital signs for effective triage prediction/update, and 4) where MERT is available, real-time casualty information to the enroute medical team as it approaches, enabling more effective crew resource management and casualty prioritisation, thereby reducing time on the ground. Trust (technically robust, ethically adherent and lawful) in ATRACT will be achieved via design and development processes which comply with the latest ethical and legal MoD AI standards, and military medical practice, incorporating principles from the WHO Surgical Checklist to align medical considerations with data quality, bias avoidance and system reliability factors. Our team possesses long-standing expertise in all areas required for this project: robotics and control engineering, machine intelligence, computer vision and AI, and military applied ethics rooted in operational experience.
Short titleATRACT
StatusActive
Effective start/end date18/04/2318/04/26

Collaborative partners

Keywords

  • Autonomous Systems
  • Robotics
  • Computer Vision
  • Artificial Intelligence
  • Drone AI
  • AI Ethics
  • Fine-grained Action Recognition

Research Institutes

  • Health Research Institute
  • Institute for Social Responsibility

Research Centres

  • Centre for Intelligent Visual Computing Research
  • Data and Complex Systems Research Centre
  • Data Science STEM Research Centre

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.