UAV-Enabled Wilderness Search and Rescue: A Human-Centered Approach

无人机荒野搜索和救援：以人为本的方法

• 批准号: 0534736
• 负责人: Michael Goodrich
• 金额: --
• 依托单位: Brigham Young University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-11-01 至 2009-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0534736&HistoricalAwards=false
• 关键词: UAV; Enabled; Wilderness; Search; Rescue

Wilderness search and rescue (WSAR) is the task of finding and giving assistance to humans who are lost or injured in mountain, desert, lake, river, or other remote settings. Because of the vast distances involved in wilderness settings, searchers frequently depend on surveillance from helicopters and small airplanes. Although these resources are very useful for searchers, the have limitations: resources consume considerable cost, there can be delays between when the resources are needed and when they arrive, ground searchers and pilots must overcome communications barriers between them, and the aircraft may not be able to provide low level imagery because of flying restrictions associated with rugged terrain. The central hypothesis of this project is that mini (3-5 foot wing spans), fixed wing Unmanned Aerial Vehicles (UAVs) can be used by WSAR personnel to efficiently find people in the wilderness. The human factors issues associated with small UAVs are much different than those associated with large UAVs, mostly because small UAVs for WSAR personnel imply limitations on operator training, sensor capacity, autonomy capability, and flight time. The PI's plan is to develop operator interfaces and UAV autonomy for WSAR systems that allow people without RC-piloting skills to search an area, using either online or offline approaches. When working online, the PI will adopt a non-pilot operator perspective and design autonomy to allow operators working in an "augmented virtuality" environment to "guide the camera" rather than fly the UAV. In situations where information from a UAV's video is to be recorded and used in offline information retrieval and analysis, the PI will pursue an active mosaic approach in which video images are overlaid on terrain maps. The PI will employ a strongly human-centered approach in all phases of the project, both for creating the WSAR systems and for evaluating them, in which expertise from researchers in human-robot interaction, computer vision, controls, and artificial intelligence is integrated. User studies will include field tests with WSAR personnel, investigation of current work practice in WSAR teams, usefulness of active mosaicing for offline and online searches, and so on.Broader Impacts: Each year, many people are lost or find themselves in jeopardy while hiking, boating/kayaking, skiing, fishing, etc. Each year, wilderness search and rescue consumes thousands of person-hours and hundreds of thousands of dollars in Utah alone. With each hour that passes between the time that a person is lost and WSAR people find the victim, the effective search radius grows by approximately 3km. Each hour spent in the water or lost in the woods decreases the likelihood of a successful rescue. A portable UAV with appropriate interfaces, autonomy, and sensor processing at an affordable price should decrease the amount of time required between when searchers arrive at a scene and the time when aerial surveillance is present to support their efforts. Such a system would increase the probability of successful rescue.

野外搜救（Wilderness Search and Rescue，WSAR）是一项在山区、沙漠、湖泊、河流或其他偏远地区寻找失踪或受伤人员并给予帮助的任务。 由于在荒野环境中涉及的广阔距离，搜索人员经常依赖直升机和小型飞机的监视。 虽然这些资源对搜索人员非常有用，但也有局限性：资源消耗相当大的成本，需要资源和资源到达之间可能存在延迟，地面搜索人员和飞行员必须克服他们之间的通信障碍，并且由于与崎岖地形相关的飞行限制，飞机可能无法提供低空图像。 该项目的中心假设是，小型（3-5英尺翼展），固定翼无人机（UAV）可以被WSAR人员用来有效地在荒野中寻找人。 与小型无人机相关的人因问题与大型无人机相关的人因问题有很大不同，主要是因为WSAR人员使用小型无人机意味着操作员培训、传感器容量、自主能力和飞行时间的限制。 PI的计划是为WSAR系统开发操作员界面和无人机自主性，允许没有遥控驾驶技能的人使用在线或离线方法搜索一个区域。 当在线工作时，PI将采用非飞行员操作员的视角和设计自主性，以允许操作员在“增强虚拟”环境中工作，以“引导相机”而不是驾驶无人机。 在记录来自无人机视频的信息并用于离线信息检索和分析的情况下，PI将采用主动镶嵌方法，其中视频图像覆盖在地形图上。 PI将在项目的所有阶段采用以人为本的方法，无论是创建WSAR系统还是对其进行评估，其中集成了研究人员在人机交互，计算机视觉，控制和人工智能方面的专业知识。 用户研究将包括与WSAR人员的实地测试、WSAR团队当前工作实践的调查、离线和在线搜索的主动镶嵌的有用性等。每年，许多人在徒步旅行、划船/皮划艇、滑雪、钓鱼等时迷路或发现自己处于危险之中。仅在犹他州，野外搜索和救援就消耗了数千人小时和数十万美元。 从一个人失踪到WSAR人员找到受害者之间每隔一个小时，有效搜索半径就会增加大约3公里。 在水中或在树林中迷失的每一个小时都减少了成功营救的可能性。 具有适当接口、自主性和传感器处理且价格合理的便携式无人机应减少搜索人员到达现场与空中监视支持其工作之间所需的时间。 这样的系统将增加成功救援的可能性。