Flexible Mechanical Metamaterials Enabled Electronic Skin for Real-Time Detection of Unstable Grasping in Robotic Manipulation

被引:116
作者
Huang, Xin [1 ]
Guo, Wei [1 ]
Liu, Shaoyu [1 ]
Li, Yangyang [1 ]
Qiu, Yuqi [1 ]
Fang, Han [1 ]
Yang, Ganguang [1 ]
Zhu, Kanhao [1 ]
Yin, Zhouping [1 ]
Li, Zhuo [2 ]
Wu, Hao [1 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, State Key Lab Digital Mfg Equipment & Technol, Flexible Elect Res Ctr, Wuhan 430074, Hubei, Peoples R China
[2] Fudan Univ, Dept Mat Sci, Shanghai 200433, Peoples R China
基金
中国国家自然科学基金;
关键词
electronic-skin; flexible auxetic metamaterials; grasping condition; real-time perception; robotics; SENSOR; TACTILE; COMPLIANT; BEHAVIOR; RATIOS; FUTURE; MEMORY; SLIP;
D O I
10.1002/adfm.202109109
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Electronic-skin (E-skin) has been investigated extensively for robotic tactile sensing. However, E-skin sensors based on flexible metamaterials are still challenging to achieve. Moreover, the implementation of E-skin sensor arrays in the actual monitoring of robotic grasping and manipulation conditions are rather limited due to the difficulty in data processing. Herein, high-performance E-skin strain sensors based on flexible auxetic metamaterials are reported, which endow the sensors with the capability of measuring both compressive (40%) and tensile (>80%) strain in a wide range and superior sensitivity, as compared with sensors without the structure. With perception data collected by the sensors, a generic method for real-time detection of unstable robotic grasping is established. Through this method, the complicated problem of processing large-scale arrayed sensor signals is simplified into the calculation of two indices, which extract both time and frequency domain characteristics of the signals. The total detection time (including sensor measurement response and data processing) can be as short as 100 ms, in line with human skin response in slippage perception. Accurate detections in real-time during various grasping and manipulation tasks are presented, demonstrating the great value of the sensors and the detection approach in robotic perception and dexterous manipulation.
引用
收藏
页数:12
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