用AI与AR技术帮搜救犬主人实时掌握犬只位置和发现情况
KHAIT: K-9 Handler Artificial Intelligence Teaming for Collaborative Sensemaking
- 通过犬视角的AI摄像头和边缘计算实现精准目标检测
- 实测使幸存者定位时间平均缩短22%，提升搜救效率
- 适合应急救援、智能穿戴设备研究者参考
在城市搜索与救援（USAR）任务中，搜救犬与训导员之间的沟通至关重要，但复杂环境及犬只特定行为常导致信息不畅。由于搜救犬常处于训导员视线之外，后者难以掌握犬只位置与状态，形成‘认知差距’。本文提出KHAIT，一种融合基于目标检测的AI与增强现实（AR）的新方法，通过配备AI摄像头、边缘计算与AR头显，从犬只视角实现快速精准的目标检测，显著提升幸存者定位能力。在真实USAR环境中评估表明，该方法使幸存者分配时间平均减少22%，有效提升搜救速度与准确性。
原文摘要 · Abstract (English)
In urban search and rescue (USAR) operations, communication between handlers and specially trained canines is crucial but often complicated by challenging environments and the specific behaviors canines are trained to exhibit when detecting a person. Since a USAR canine often works out of sight of the handler, the handler lacks awareness of the canine's location and situation, known as the 'sensemaking gap.' In this paper, we propose KHAIT, a novel approach to close the sensemaking gap and enhance USAR effectiveness by integrating object detection-based Artificial Intelligence (AI) and Augmented Reality (AR). Equipped with AI-powered cameras, edge computing, and AR headsets, KHAIT enables precise and rapid object detection from a canine's perspective, improving survivor localization. We evaluate this approach in a real-world USAR environment, demonstrating an average survival allocation time decrease of 22%, enhancing the speed and accuracy of operations.
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