Over 600,000 bridges in the U.S. must be inspected every two years to identify flaws, defects, or potential problems that may need follow-up maintenance. Bridge inspection has adopted unmanned aerial vehicles (or drones) for improving safety, efficiency, and cost-effectiveness. Although drones can operate in an autonomous mode, keeping inspectors in the loop is critical for complex tasks in bridge inspection. Therefore, inspectors need to develop the skill and confidence to operate drones in their jobs. This paper presents the design and development of a virtual reality-based training and assessment system for inspectors assisted by a drone in bridge inspection. The system is composed of four integrated modules: a simulated bridge inspection developed in Unity, an interface that allows a trainee to operate the drone in simulation using a remote controller, data monitoring and analysis to provide real-time, in-task feedback to trainees to assist their learning, and a post-study assessment supporting personalized training. The paper also conducts a proof-of-concept pilot study to illustrate the functionality of this system. The study demonstrated that TASBID, as a tool for the early-stage training, can objectively identify the training needs of individuals in detail and, further, help them develop the skill and confidence in collaborating with a drone in bridge inspection. The system has built a modeling and analysis platform for exploring advanced solutions to the human-drone cooperative inspection of civil infrastructure.
翻译:美国境内600 000多座桥梁必须每两年检查一次,以查明可能需要后续维修的缺陷、缺陷或潜在问题。桥梁检查采用了无人驾驶飞行器(或无人驾驶飞机),以提高安全、效率和成本效益。虽然无人驾驶飞机可以自主运作,但让检查员进入环路对于桥梁检查的复杂任务至关重要。因此,检查员需要发展在其岗位上操作无人驾驶飞机的技能和信心。本文件介绍了设计并开发一个虚拟的现实培训和评估系统,由无人驾驶飞机协助进行桥梁检查。该系统由四个综合模块组成:在团结公司开发的模拟桥梁检查,这一界面使受训人员能够在模拟中使用无人驾驶飞机,使用远程控制器、数据监测和分析,向受训人员提供实时、即时反馈,以协助他们学习,并进行后期评估,支持个人化培训。该文件还进行了一项概念验证试点研究,以说明该系统的功能。该研究显示,作为早期培训工具,土耳其航天局可以客观地确定个人在模拟中操作无人驾驶飞机,利用远程控制器、数据监测和分析,为受训人员提供实时反馈,向受训人员提供支持学习,并进一步发展空间视察平台的合作技术。