A Large‐Area, Stretchable, Textile‐Based Tactile Sensor
A tactile sensor is a necessary means for intelligent equipment to acquire external environment information and improve the performance of human–robot interaction. Although high‐performance tactile sensor array is widely studied, the large number of wires required to transmit data from numerous arra...
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Veröffentlicht in: | Advanced materials technologies 2020-04, Vol.5 (4), p.n/a |
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Sprache: | eng |
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Zusammenfassung: | A tactile sensor is a necessary means for intelligent equipment to acquire external environment information and improve the performance of human–robot interaction. Although high‐performance tactile sensor array is widely studied, the large number of wires required to transmit data from numerous arrays is still a major obstacle in large‐area application. In this study, a large‐area, low‐cost, stretchable, textile‐based tactile sensor, which is sensitive for contact position, is proposed. The sensor has a simple three‐layer structure and four external wires due to the use of a novel double‐faced effect functional knitted textile with “self‐uniformity” characteristic. The porous polyurethane foam with a large pore size is first reported as touch switch material. It not only has excellent touch switch function, but also makes the sensor have a soft and elastic touch and good impact buffering. In addition, the application of radial basis function neural network makes the sensor have self‐learning “intelligence,” which makes the sensor flexibly and quickly arrange even on the surface of a complex 3D object. Finally, the potential applications of the sensor are demonstrated. This study shows that the sensor has great potential in the fields of wearable devices, robot interaction control, and human–computer interface.
A large‐area, stretchable, textile‐based tactile sensor with position detection is proposed. It has a simple three‐layer structure and four wires due to use of a novel double‐faced effect functional knitted textile. By using radial basis function (RBF) neural network, the sensor can be quickly arranged even on the surface of complex 3D object. |
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ISSN: | 2365-709X 2365-709X |
DOI: | 10.1002/admt.201901060 |