ATRACT: A Trustworthy Robotic Autonomous system to support Casualty Triage

ATRACT：一个值得信赖的机器人自主系统，支持伤员分类

• 批准号: EP/X028631/1
• 负责人: Ardhendu Behera
• 金额: $ 110.73万
• 依托单位: Edge Hill University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX028631%2F1
• 关键词: ATRACT; Trustworthy; Robotic; Autonomous; system

In the Vietnam War, American evacuation helicopters transformed soldier survivability with the emergence of the 'Golden Hour'. This relied on air superiority and relative freedom of movement and has been the UK/US/NATO approach to battlefield casualty treatment since. However, recent proliferation and effectiveness of low-cost, accurate, shoulder-launched ground-to-air missiles has significantly disrupted helicopter operations in Ukraine and thus, presenting a heightened risk to Casualty Evacuation (CASEVAC) operations. Moreover, frontline army doctors work in world's most harsh and hostile environments, and often risk their lives while marching out and stepping in when they are needed near fighting forces. They are often required to monitor multiple casualties at a given time and prioritise whom they should be attending first based on the severity of injuries. Thus, there is an urgent unmet need for enhancing casualty survival in a contested environment where conventional helicopter CASEVAC is slow or unavailable.Recent advancement in Artificial Intelligence (AI) and Robotic Autonomous System (RAS) provides new and future opportunities to meet this challenge. In line with this, the proposed ATRACT system is a disruptive innovation to address this unmet need in a novel way by designing, developing and field-testing a trustworthy drone-driven RAS to help frontline medics in decision-making in the first 'platinum ten minutes' following trauma. ATRACT will adopt 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 algorithms for a robotic system to detect frontline soldiers, 3) real-time monitoring of their injury severity and vital signs for effective triage prediction/update, and 4) where medical emergency response team 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 to maximise survivability and to minimise risk of the frontline medics being attacked. AI and RAS are the driving forces in many industries (e.g., manufacturing, agriculture, transport, healthcare, etc.) and helping to address some of the most pressing issues facing humankind. Many such technologies have a major limitation of trustworthiness (technically robust, ethically adherent and lawful) and mainly because they typically use a "black box" approach, where AI elements are often less visible and transparent in the way data is used and operationalised from multiple sources, and frequently exhibits unconscious biases resulting in lack of control in decision-making. Moreover, they do not provide contextualised services or customised interventions to changing conditions and/or environmental settings. ATRACT will address these limitations 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. We will ensure that ATRACT is transparent, consistent and interpretable so that potential bias, legal and medical compliance, and MoD ethics can be addressed systematically at every stage of design, development and testing with expert-in-the-loop. Successful results in this context will revolutionise the way frontline health services, casualty evacuation and the delivery of emergency and lifesaving medical aid is delivered, resulting in significant health, social and economic benefits.

在越南战争中，美国疏散直升机随着“黄金时刻”的出现改变了士兵的生存能力。这依赖于空中优势和相对的行动自由，并且一直是英国/美国/北约处理战场伤亡的方法。然而，最近低成本、精确、肩射地对空导弹的扩散和有效性严重扰乱了乌克兰的直升机行动，从而给伤亡后送（CASEVAC）行动带来了更大的风险。此外，前线军医在世界上最恶劣和最恶劣的环境中工作，当战斗部队需要他们时，他们经常冒着生命危险前行和介入。他们通常需要在给定时间监视多名伤员，并根据受伤的严重程度优先考虑应该首先照顾的人员。因此，在传统直升机紧急救援速度缓慢或不可用的竞争环境中，迫切需要提高伤员的生存能力。人工智能 (AI) 和机器人自主系统 (RAS) 的最新进展为应对这一挑战提供了新的和未来的机会。与此相一致的是，拟议的 ATRACT 系统是一项颠覆性创新，通过设计、开发和现场测试值得信赖的无人机驱动的 RAS，以一种新颖的方式解决这一未满足的需求，以帮助一线医务人员在创伤后的第一个“白金十分钟”内做出决策。 ATRACT 将采用跨学科和变革性的研究方法，重点关注：1）在困难地形中使用无人机的先进操纵技术精确搜索和定位受伤士兵；2）一个新颖的平台，结合了先进的多模态传感和超越最先进算法的机器人系统来检测前线士兵；3）实时监测他们的受伤严重程度和生命体征，以进行有效的分类预测/更新；4）在哪里 医疗应急响应小组可以在航路医疗队接近时向其提供实时伤亡信息，从而实现更有效的机组资源管理和伤亡优先顺序，从而减少在地面上的时间，最大限度地提高生存能力并最大限度地减少前线医务人员受到攻击的风险。人工智能和RAS是许多行业（例如制造业、农业、运输、医疗保健等）的驱动力，有助于解决人类面临的一些最紧迫的问题。许多此类技术在可信度方面存在重大限制（技术稳健、道德遵守和合法），主要是因为它们通常使用“黑匣子”方法，其中人工智能元素在使用和操作多个来源的数据的方式上往往不太明显和透明，并且经常表现出无意识的偏见，导致决策缺乏控制。此外，他们不针对不断变化的条件和/或环境设置提供情境化服务或定制干预措施。 ATRACT 将通过符合最新道德和法律国防部人工智能标准以及军事医疗实践的设计和开发流程来解决这些限制，并结合世界卫生组织外科检查表的原则，使医疗考虑因素与数据质量、避免偏差和系统可靠性因素保持一致。我们将确保 ATRACT 是透明的、一致的和可解释的，以便在设计、开发和测试的每个阶段都可以由专家在环系统地解决潜在的偏见、法律和医疗合规性以及国防部道德问题。在这方面的成功成果将彻底改变一线卫生服务、伤员后送以及提供紧急和救生医疗援助的方式，从而产生显着的健康、社会和经济效益。

项目成果

Exploiting Label Uncertainty for Enhanced 3D Object Detection From Point Clouds

• DOI: 10.1109/tits.2023.3334873
• 发表时间: 2024-06
• 期刊: IEEE Transactions on Intelligent Transportation Systems
• 影响因子: 8.5
• 作者: Yan Sun;Bin Lu;Yonghuai Liu;Zhenyu Yang;Ardhendu Behera;Ran Song;Hejin Yuan;Haiyan Jiang

Intelligent Systems and Pattern Recognition - Third International Conference, ISPR 2023, Hammamet, Tunisia, May 11-13, 2023, Revised Selected Papers, Part II

智能系统和模式识别 - 第三届国际会议，ISPR 2023，突尼斯哈马马特，2023 年 5 月 11-13 日，修订后的精选论文，第二部分

• DOI: 10.1007/978-3-031-46338-9_12
• 发表时间: 2024
• 作者: Artaud C

Towards Self-Adaptive Resilient Swarms Using Multi-Agent Reinforcement Learning

• DOI: 10.5220/0012462800003654
• 发表时间: 2024
• 作者: Rafael Pina;V. D. Silva;Corentin Artaud