Gesture recording,modeling,and understanding based on a robust electronic glove(E-glove)are of great significance for efficient human-machine cooperation in harsh environments.However,such robust edge-intelligence int...Gesture recording,modeling,and understanding based on a robust electronic glove(E-glove)are of great significance for efficient human-machine cooperation in harsh environments.However,such robust edge-intelligence interfaces remain challenging as existing E-gloves are limited in terms of integration,waterproofness,scalability,and interface stability between different components.Here,we report on the design,manufacturing,and application scenarios for a waterproof E-glove,which is of low cost,lightweight,and scalable for mass production,as well as environmental robustness,waterproofness,and washability.An improved neural network architecture is proposed to implement environment-adaptive learning and inference for hand gestures,which achieves an amphibious recognition accuracy of 100%in 26 categories by analyzing 2,600 hand gesture patterns.We demonstrate that the E-glove can be used for amphibious remote vehicle navigation via hand gestures,potentially opening the way for efficient human-human and human-machine cooperation in harsh environments.展开更多
提出了一种基于PPT(precision position tracker)跟踪器和Cyber手套的虚拟手交互方法,该方法先是通过PPT跟踪器获取人手的空间方位和移动数据以及通过Cyber手套获取手指各关节的运动数据;接着构建相应的数据结构,关联数据手套、位置跟...提出了一种基于PPT(precision position tracker)跟踪器和Cyber手套的虚拟手交互方法,该方法先是通过PPT跟踪器获取人手的空间方位和移动数据以及通过Cyber手套获取手指各关节的运动数据;接着构建相应的数据结构,关联数据手套、位置跟踪器和虚拟手,驱动虚拟手操作,实现虚拟手在3D虚拟环境中的自然交互。实验结果表明此方法可以实时地获取数据手套运动数据并控制虚拟手操作,视觉效果良好,交互行为直观。展开更多
基金supported by the National Natural Science Foundation of China(Nos.62075040 and 51603227)the National Key R&D Program of China(No.2017YFE0112000)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX22_0230).
文摘Gesture recording,modeling,and understanding based on a robust electronic glove(E-glove)are of great significance for efficient human-machine cooperation in harsh environments.However,such robust edge-intelligence interfaces remain challenging as existing E-gloves are limited in terms of integration,waterproofness,scalability,and interface stability between different components.Here,we report on the design,manufacturing,and application scenarios for a waterproof E-glove,which is of low cost,lightweight,and scalable for mass production,as well as environmental robustness,waterproofness,and washability.An improved neural network architecture is proposed to implement environment-adaptive learning and inference for hand gestures,which achieves an amphibious recognition accuracy of 100%in 26 categories by analyzing 2,600 hand gesture patterns.We demonstrate that the E-glove can be used for amphibious remote vehicle navigation via hand gestures,potentially opening the way for efficient human-human and human-machine cooperation in harsh environments.
文摘提出了一种基于PPT(precision position tracker)跟踪器和Cyber手套的虚拟手交互方法,该方法先是通过PPT跟踪器获取人手的空间方位和移动数据以及通过Cyber手套获取手指各关节的运动数据;接着构建相应的数据结构,关联数据手套、位置跟踪器和虚拟手,驱动虚拟手操作,实现虚拟手在3D虚拟环境中的自然交互。实验结果表明此方法可以实时地获取数据手套运动数据并控制虚拟手操作,视觉效果良好,交互行为直观。
