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用于重建物理和虚拟抓取的可重构数据手套 Article
刘航欣, 张泽宇, 焦子元, Zhenliang Zhang, Minchen Li, 蒋陈凡夫, 朱毅鑫, Song-Chun Zhu
《工程(英文)》 2024年 第32卷 第1期 页码 203-220 doi: 10.1016/j.eng.2023.01.009
In this work, we present a reconfigurable data glove design to capture different modes of human hand–object interactions, which are critical in training embodied artificial intelligence (AI) agents for fine manipulation tasks. To achieve various downstream tasks with distinct features, our reconfigurable data glove operates in three modes sharing a unified backbone design that reconstructs hand gestures in real time. In the tactile-sensing mode, the glove system aggregates manipulation force via customized force sensors made from a soft and thin piezoresistive material; this design minimizes interference during complex hand movements. The virtual reality (VR) mode enables real-time interaction in a physically plausible fashion: A caging-based approach is devised to determine stable grasps by detecting collision events. Leveraging a state-of-the-art finite element method, the simulation mode collects data on fine-grained four-dimensional manipulation events comprising hand and object motions in three-dimensional space and how the object's physical properties (e.g., stress and energy) change in accordance with manipulation over time. Notably, the glove system presented here is the first to use high-fidelity simulation to investigate the unobservable physical and causal factors behind manipulation actions. In a series of experiments, we characterize our data glove in terms of individual sensors and the overall system. More specifically, we evaluate the system's three modes by ① recording hand gestures and associated forces, ② improving manipulation fluency in VR, and ③ producing realistic simulation effects of various tool uses, respectively. Based on these three modes, our reconfigurable data glove collects and reconstructs fine-grained human grasp data in both physical and virtual environments, thereby opening up new avenues for the learning of manipulation skills for embodied AI agents.
关键词: Data glove Tactile sensing Virtual reality Physics-based simulation
一种具有大工作空间的轻量级力反馈手套 Article
郑宇铠, 王党校, 王子琦, 张昱, 张玉茹, 徐卫良
《工程(英文)》 2018年 第4卷 第6期 页码 869-880 doi: 10.1016/j.eng.2018.10.003
在虚拟现实场景中,佩戴力反馈手套是一种有效的增强穿戴者与虚拟物体交互沉浸感的方法。这种手套的设计难点在于需要提供足够大的手指运动工作空间,在模拟自由空间和约束空间交互时提供所需的力反馈感觉,以及确保一个轻量级的结构。本文提出了一种将气动驱动器安装在使用者手背侧的力反馈手套。该手套采用了一种凸轮连杆组合机构,利用带有弯曲滑槽和三个运动副的连杆将阻力从气缸活塞杆传递到指尖。为了得到穿戴者指尖反馈力的一个较大的法向分量,通过分析带有三个运动副的连杆上的力平衡,计算出了滑槽的轮廓。本文研制了质量为245 g 的五指力反馈手套样机,建立了可穿戴的力测量系统,对自由空间和约束空间的力反馈性能进行了定量评价。实验结果表明,该手套在自由空间模拟中平均阻力小于0.1 N,在约束空间模拟中指尖力最大为4 N。实验进一步证实,这种手套能够保证手指的自由移动以及模拟典型的抓取操作手势。
A review of systematic evaluation and improvement in the big data environment
Feng YANG, Manman WANG
《工程管理前沿(英文)》 2020年 第7卷 第1期 页码 27-46 doi: 10.1007/s42524-020-0092-6
关键词: big data evaluation methods systematic improvement big data analytic techniques data mining
《环境科学与工程前沿(英文)》 2023年 第17卷 第8期 doi: 10.1007/s11783-023-1694-0
● Data quality assessment criteria for MP/NPs in food products were developed.
关键词: Microplastic Nanoplastic Food products Data quality Human health risk
Blockchain application in healthcare service mode based on Health Data Bank
Jianxia GONG, Lindu ZHAO
《工程管理前沿(英文)》 2020年 第7卷 第4期 页码 605-614 doi: 10.1007/s42524-020-0138-9
关键词: Health Data Bank blockchain data assets smart contract incentive mechanism
Challenges to Engineering Management in the Big Data Era
Yong Shi
《工程管理前沿(英文)》 2015年 第2卷 第3期 页码 293-303 doi: 10.15302/J-FEM-2015042
关键词: big data data science intelligent knowledge engineering management real-life applications
Intelligent data analytics is here to change engineering management
Jonathan Jingsheng SHI, Saixing ZENG, Xiaohua MENG
《工程管理前沿(英文)》 2017年 第4卷 第1期 页码 41-48 doi: 10.15302/J-FEM-2017003
关键词: engineering management project management big data data analytics planning execution
Special issue: Innovative applications of big data and artificial intelligence
《工程管理前沿(英文)》 2022年 第9卷 第4期 页码 517-519 doi: 10.1007/s42524-022-0234-0
Anensemble method for data stream classification in the presence of concept drift
Omid ABBASZADEH,Ali AMIRI,Ali Reza KHANTEYMOORI
《信息与电子工程前沿(英文)》 2015年 第16卷 第12期 页码 1059-1068 doi: 10.1631/FITEE.1400398
关键词: Data stream Classificaion Ensemble classifiers Concept drift
Nicolas MUNIER-JOLAIN, Martin LECHENET
《农业科学与工程前沿(英文)》 2020年 第7卷 第1期 页码 21-27 doi: 10.15302/J-FASE-2019292
Redesigning cropping and farming systems to enhance their sustainability is mainly addressed in scientific studies using experimental and modeling approaches. Large data sets collected from real farms allow for the development of innovative methods to produce generic knowledge. Data mining methods allow for the diversity of systems to be considered holistically and can take into account the diversity of production contexts to produce site-specific results. Based on the very few known studies using such methods to analyze the crop management strategies affecting pesticide use and their effect on farm performance, we advocate further investment in the development of large data sets that can support future research programs on farming system design.
关键词: data mining holistic Integrated Pest Management economics DEPHY network.
《能源前沿(英文)》 doi: 10.1007/s11708-023-0912-6
关键词: model predictive control interconnected data center multi-timescale optimized scheduling distributed power supply landscape uncertainty
Big data and machine learning: A roadmap towards smart plants
《工程管理前沿(英文)》 页码 623-639 doi: 10.1007/s42524-022-0218-0
关键词: big data machine learning artificial intelligence smart sensor cyber–physical system Industry 4.0 intelligent system digitalization
Clinical research of traditional Chinese medicine in big data era
null
《医学前沿(英文)》 2014年 第8卷 第3期 页码 321-327 doi: 10.1007/s11684-014-0370-y
With the advent of big data era, our thinking, technology and methodology are being transformed. Data-intensive scientific discovery based on big data, named “The Fourth Paradigm,” has become a new paradigm of scientific research. Along with the development and application of the Internet information technology in the field of healthcare, individual health records, clinical data of diagnosis and treatment, and genomic data have been accumulated dramatically, which generates big data in medical field for clinical research and assessment. With the support of big data, the defects and weakness may be overcome in the methodology of the conventional clinical evaluation based on sampling. Our research target shifts from the “causality inference” to “correlativity analysis.” This not only facilitates the evaluation of individualized treatment, disease prediction, prevention and prognosis, but also is suitable for the practice of preventive healthcare and symptom pattern differentiation for treatment in terms of traditional Chinese medicine (TCM), and for the post-marketing evaluation of Chinese patent medicines. To conduct clinical studies involved in big data in TCM domain, top level design is needed and should be performed orderly. The fundamental construction and innovation studies should be strengthened in the sections of data platform creation, data analysis technology and big-data professionals fostering and training.
关键词: big data traditional Chinese medicine clinical evaluation evidence based medicine
Appreciating the role of big data in the modernization of environmental governance
《工程管理前沿(英文)》 2022年 第9卷 第1期 页码 163-169 doi: 10.1007/s42524-021-0185-x
A building-based data capture and data mining technique for air quality assessment
Ni SHENG, U Wa TANG
《环境科学与工程前沿(英文)》 2011年 第5卷 第4期 页码 543-551 doi: 10.1007/s11783-011-0369-4
关键词: traffic air pollution spatial distribution high resolution geographic information system
标题 作者 时间 类型 操作
A review of systematic evaluation and improvement in the big data environment
Feng YANG, Manman WANG
期刊论文
Data quality assessment for studies investigating microplastics and nanoplastics in food products: Arecurrent data reliable?
期刊论文
Blockchain application in healthcare service mode based on Health Data Bank
Jianxia GONG, Lindu ZHAO
期刊论文
Intelligent data analytics is here to change engineering management
Jonathan Jingsheng SHI, Saixing ZENG, Xiaohua MENG
期刊论文
Anensemble method for data stream classification in the presence of concept drift
Omid ABBASZADEH,Ali AMIRI,Ali Reza KHANTEYMOORI
期刊论文
Methodological considerations for redesigning sustainable cropping systems: the value of data-mininglarge and detailed farm data sets at the cropping system level
Nicolas MUNIER-JOLAIN, Martin LECHENET
期刊论文
Multi-timescale optimization scheduling of interconnected data centers based on model predictive control
期刊论文