Leverage Augmented Reality for Safety Education in the Logistics Industry

该项目将设计和研究一种沉浸式和个性化的教育方法，利用增强现实（AR）来支持工人了解与工作相关的风险因素，并鼓励工人使用适当的身体动作来完成任务。该项目将开发一种ar辅助姿势训练程序，以最大限度地减少下背部和肩部的生物力学暴露，因为这两个身体部位在物流行业中最常见。这项研究将扩展ar辅助教育和培训方面的知识，包括促进工作安全、运动适应和学习转移。增强现实基础设施还可以用于提供及时的工作流程培训，并在高中和大学物理和生物力学课程中有潜在的应用。该项目将推进运动学习方面的研究，如运动训练和远程康复。总体结果将推动人体运动教育和学习科学的人类技术体系。项目团队将重建一个虚拟教练，演示在物料搬运中常见的推荐和不推荐的身体动作。AR、深度传感和生物力学建模将被整合，以提供与工作相关的关节和肌肉生物力学暴露的知识。员工将能够通过增强现实眼镜从不同角度观察覆盖在实际物理工作场所上的虚拟教练。该系统旨在通过抽象生物力学暴露的可视化来提高工人对工作相关风险的理解。生物力学暴露，如在工作中施加在关节和肌肉上的力，将在视觉上与虚拟教练相结合。生物力学暴露的创新几何表示将帮助学习者可视化抽象力学量。AR用户界面和生物力学可视化方案将通过一系列可用性评估和操作测试进行迭代完善，以确保工人了解肌肉骨骼疾病的风险。该研究还将研究人工智能辅助安全教育方法中的工人学习和学习转移。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The project will design and research an immersive and personalized education approach by leveraging augmented reality (AR) to support workers' understanding of risk factors associated with their work, and encourage workers to perform tasks using appropriate body motion. The project will develop an AR-assisted posture training procedure for minimizing biomechanical exposures on the low back and the shoulder, as injuries of those two body regions are the most common in logistics industry. The research will expand knowledge in AR-assisted education and training in terms of work safety promotion, motor adaptation, and transfer of learning. The AR infrastructure can also used to provide just-in-time work procedure training and has potential applications in high school and college courses in physics and biomechanics. The project will advance research in to motor learning, such as sports training and tele-rehabilitation. The overall outcome will advance human-technology system in body motion education and learning science.The project team will reconstruct a virtual instructor demonstrating the recommended and non-recommended body motions that are commonly seen in material handling. AR, depth sensing, and biomechanical modeling will be integrated to deliver knowledge on work-related biomechanical exposures on joints and muscles. Workers will be able to observe the virtual instructor overlaid on the actual physical workplace from various view angles through AR goggles. The system will be designed to enhance workers' understanding of work-related risks via visualization of abstract biomechanical exposures. Biomechanical exposures, such as forces exerted on the joints and the muscles at work, will be visually integrated with the virtual instructor. The innovative geometric representation of biomechanical exposures will assist learners in visualizing abstract mechanics quantities. The AR user interface and the biomechanical visualization scheme will be iteratively refined through a series of usability evaluations and operational tests to ensure worker's understanding of the risk in musculo-skeletal disorder. The research will also examine worker learning and transfer of learning in AR-assisted safety education approach.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.