ACE-OPS: From Autonomy to Cognitive assistance in Emergency OPerationS

ACE-OPS：紧急行动中从自主到认知协助

• 批准号: EP/S030832/1
• 负责人: Niki Trigoni
• 金额: $ 154.82万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FS030832%2F1
• 关键词: ACE; OPS; Autonomy; Cognitive; assistance

The vision of this collaborative multi-centre project is to safeguard and transform current operation protocols of emergency teams by providing sensing, situation awareness, cognitive assistance and mobile autonomy capabilities working synergistically as a single system. Statistics collected by the Home Office report 346 fire related fatalities in England during 2016/2017, the highest figure since 2011/12. Over a 10-year period in USA, 2775 firefighters died on duty. Where there is a need to save and evacuate people from a burning or flooded building, it is important for the chief incident commander to have increased situational awareness and to be able to effectively coordinate the rescue operation, and for individual responders to have enhanced visibility of surrounding hazards and dangers. To this end, we need to combine UK-based expertise in mobile autonomy and people localisation, with internationally leading expertise on welfare monitoring and cognitive assistance at the Univ. of Virginia, and on robotic vision applied to aerial vehicles at the Queensland University of Technology. The proposed work involves four distinct research directions: 1) providing an integrated system for situation awareness that involves localisation of the emergency responders, monitoring of their welfare and mapping of the dynamically changing environment; 2) exploring how situation awareness information should be fed into cognitive assistance tools, in order to provide helpful triggers and alerts to the incident commander and their team; 3) introducing various levels of autonomy enabling aerial vehicles to simultaneously perform tasks of mapping, communication and localisation; and 4) integrating the above capabilities and building the first end-to-end response system that implements the full feedback loop from sensor acquisition to emergency responders and back to sensor actuation. Sensors on people's wearable devices together with sensors mounted on aerial vehicles will contribute to data acquisition for welfare, location and environment monitoring. This in turn will provide input to cognitive assistance for emergency response teams, helping them to assess the situation. They will then in turn provide feedback to sensor systems to prioritise monitoring of specific areas, people or tasks, thus dynamically influencing the next round of situation awareness, and so on. This feedback loop will be a step change providing a whole new approach to safety for emergency responders.

这一多中心协作项目的愿景是通过提供传感、态势感知、认知协助和移动的自主能力，作为一个单一系统协同工作，保护和改变应急小组目前的行动协议。内政部收集的统计数据显示，2016/2017年度英格兰有346起火灾死亡，这是自2011/12年度以来的最高数字。在过去的10年里，美国有2775名消防员因公殉职。如果需要从燃烧或被淹的建筑物中拯救和疏散人员，重要的是首席事故指挥官必须提高态势感知能力，并能够有效地协调救援行动，并提高周围危害和危险的可见度。为此，我们需要将英国在移动的自主和人员本地化方面的专业知识与弗吉尼亚大学在福利监测和认知辅助方面的国际领先专业知识以及昆士兰州科技大学在应用于飞行器的机器人视觉方面的专业知识相结合。拟议的工作涉及四个不同的研究方向：1）提供一个综合的情况感知系统，包括应急响应人员的本地化，监测他们的福利和动态变化的环境地图; 2）探索如何将情况感知信息输入认知辅助工具，以便为事故指挥官及其团队提供有用的触发和警报; 3）引入各种级别的自主性，使飞行器能够同时执行测绘，通信和定位任务;以及4）集成上述功能并构建第一个端到端响应系统，该系统实现从传感器采集到紧急响应人员再回到传感器驱动的完整反馈回路。人们可穿戴设备上的传感器以及安装在飞行器上的传感器将有助于福利，位置和环境监测的数据采集。这反过来将为应急小组的认知援助提供投入，帮助他们评估局势。然后，它们将反过来向传感器系统提供反馈，以优先监测特定区域、人员或任务，从而动态影响下一轮的态势感知，等等。这种反馈回路将是一个重大变化，为应急响应人员提供全新的安全方法。

项目成果

A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine Intelligence

• 发表时间: 2020-06
• 期刊: ArXiv
• 作者: Changhao Chen;B. Wang;Chris Xiaoxuan Lu;A. Trigoni;A. Markham

SelfVIO: Self-supervised deep monocular Visual-Inertial Odometry and depth estimation

• DOI: 10.1016/j.neunet.2022.03.005
• 发表时间: 2022-03-18
• 期刊: NEURAL NETWORKS
• 影响因子: 7.8
• 作者: Almalioglu, Yasin;Turan, Mehmet;Trigoni, Niki
• 通讯作者: Trigoni, Niki

Deep Learning for Visual Localization and Mapping: A Survey

• DOI: 10.48550/arxiv.2308.14039
• 发表时间: 2023-08
• 期刊: IEEE transactions on neural networks and learning systems
• 影响因子: 10.4
• 作者: Changhao Chen;Bing Wang;Chris Xiaoxuan Lu;Niki Trigoni;A. Markham

Autonomous aerial mapping and its applications for emergency response

自主航空测绘及其在应急响应中的应用

• 发表时间: 2022
• 作者: Border R

The Surface Edge Explorer (SEE): A measurement-direct approach to next best view planning

Surface Edge Explorer (SEE)：用于下一个最佳视图规划的直接测量方法

• DOI: 10.48550/arxiv.2207.13684
• 发表时间: 2022
• 作者: Border R