Robot-Assisted Haptic Rendering for Nail Hammering: A Representative of IADL Tasks

被引:3
|
作者
Zhang, Changqi [1 ]
Wang, Cui [1 ,2 ]
Li, Ping [1 ]
Liu, Yudong [1 ]
Chen, Yi-Feng [1 ]
Zhang, Mingming [1 ]
机构
[1] Southern Univ Sci & Technol, Dept Biomed Engn, Shenzhen Key Lab Smart Healthcare Engn, Guangdong Prov Key Lab Adv Biomat, Nanshan 518055, Shenzhen, Peoples R China
[2] City Univ Hong Kong, Dept Biomed Engn, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Task analysis; Robots; Haptic interfaces; Rendering (computer graphics); Force; Nails; Computational modeling; Haptic modeling and rendering; instrumental activities of daily living (IADLs); nail hammering; robot; EXOSKELETON; SIMULATION; STIFFNESS; DRIVEN; CONTROLLER; MODEL;
D O I
10.1109/TASE.2023.3291751
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Restoring the capability to perform instrumental activities of daily living (IADLs) is an imperative step towards independent living for neurologically impaired individuals. Robot-assisted task-oriented training with haptic feedback has the potential to enhance patients' ability to perform IADLs. However, robot-assisted haptic rendering of IADLs is extremely challenging due to their complex dynamic properties and has been rarely reported. Considering the broad impedance range characteristics from free motion to hard contact, nail hammering (NH) is chosen as a representative IADL task. This paper presents our attempts to render the NH task via a customized robot. The core technologies consist of two aspects: 1) a robot-assisted haptic modeling technique with guaranteed accuracy and computation cost (by combining practical measurement data and experience-dependent analytical functions); 2) a robot-assisted haptic rendering technique involving a haptic robot with broad impedance range and sufficient force feedback (via a low gear ratio cable transmission and redundant actuation parallel mechanism) and closed-loop impedance control with guaranteed passivity and stability. Human experiments demonstrate an accurate NH task rendering that all Pearson correlation coefficients between real and virtual tasks are larger than 0.89. The modeling sensitivity analysis showed that stiffness parameter has the greatest effect on the realism of haptic rendering, with an effect size of 0.94. This study represents an important step towards comprehensive robot-assisted task-oriented therapy with haptic feedback.
引用
收藏
页码:4028 / 4041
页数:14
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