Leverage Augmented Reality for Safety Education in the Logistics Industry

利用增强现实进行物流行业的安全教育

• 批准号: 1822477
• 负责人: Xu Xu
• 金额: $ 74.95万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1822477&HistoricalAwards=false
• 关键词: Leverage; Augmented; Reality; Safety; Education

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.

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）来支持工人对与其工作相关的风险因素的理解，并鼓励工人使用适当的身体运动来执行任务。该项目将开发一种AR辅助姿势训练程序，以尽量减少下背部和肩部的生物力学暴露，因为这两个身体区域的损伤在物流行业中最常见。该研究将扩大AR辅助教育和培训在工作安全促进，运动适应和学习转移方面的知识。AR基础设施还可用于提供即时工作程序培训，并在高中和大学物理学和生物力学课程中具有潜在应用。该项目将推进运动学习的研究，如运动训练和远程康复。 整个成果将推进人体运动教育和学习科学的人类技术系统。项目团队将重建一个虚拟教师，演示材料处理中常见的推荐和非推荐身体运动。AR、深度传感和生物力学建模将被整合，以提供与关节和肌肉工作相关的生物力学暴露知识。工人将能够通过AR护目镜从各种视角观察覆盖在实际物理工作场所上的虚拟教练。该系统的设计将通过抽象的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。生物力学的展示，如在工作中施加在关节和肌肉上的力，将与虚拟教练在视觉上集成。创新的几何表示的生物力学暴露将有助于学习者在可视化抽象力学量。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优化，以确保工作人员了解肌肉骨骼疾病的风险。该研究还将考察在AR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NSF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。

项目成果

Recognition of driving distraction using driver's motion and deep learning

利用驾驶员动作和深度学习识别驾驶分心

• 发表时间: 2020
• 期刊: Proceedings of the 2020 IISE Annual Conference
• 作者: Xie, Z.

Attentive Normalization

• DOI: 10.1007/978-3-030-58520-4_5
• 发表时间: 2019-08
• 作者: Xilai Li;Wei Sun-;Tianfu Wu

NOPE-SAC: Neural One-Plane RANSAC for Sparse-View Planar 3D Reconstruction

• DOI: 10.1109/tpami.2023.3314745
• 发表时间: 2022-11
• 期刊: IEEE Transactions on Pattern Analysis and Machine Intelligence
• 影响因子: 23.6
• 作者: Bin Tan;Nan Xue;Tianfu Wu;Guisong Xia

A novel vision-based real-time method for evaluating postural risk factors associated with musculoskeletal disorders

• DOI: 10.1016/j.apergo.2020.103138
• 发表时间: 2020-09-01
• 期刊: APPLIED ERGONOMICS
• 影响因子: 3.2
• 作者: Li, Li;Martin, Tara;Xu, Xu
• 通讯作者: Xu, Xu

CGBA: Curvature-aware Geometric Black-box Attack

• DOI: 10.1109/iccv51070.2023.00018
• 发表时间: 2023-08
• 期刊: 2023 IEEE/CVF International Conference on Computer Vision (ICCV)
• 作者: Md. Farhamdur Reza;A. Rahmati;Tianfu Wu;H. Dai