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Robotic Hands with Intrinsic Tactile Sensing via 3D Printed Soft Pressure Sensors
- Source :
- Advanced Intelligent Systems, Vol 2, Iss 6, Pp n/a-n/a (2020)
- Publication Year :
- 2019
- Publisher :
- Wiley, 2019.
-
Abstract
- Herein, the development of complex 3D intelligent structures such as robotic hands using innovative designs and multimaterial additive manufacturing technology is presented. The distal phalanges of the 3D printed hand presented herein have inherent soft capacitive touch or pressure sensors and embedded electronics. Materials such as thermoplastic polyurethane (TPU), silver paint, conductive polylactic acid composite, graphite ink, etc. are explored to develop five different variants of the sensors using a modified 3D printer, which is capable of extruding conductive ink, metal paste, and polymers. The best‐performing 3D printed soft capacitive touch sensors, formed with silver paint and soft rubber (Ecoflex 00‐30), are integrated on the distal phalanges of the 3D printed robotic hand. These sensors exhibit a stable response with sensitivity of 0.00348 kPa−1 for pressure [less than] 10 kPa and 0.00134 kPa−1 for higher pressure. To demonstrate the practical applicability, the 3D printed hand with embedded soft capacitive touch sensors is used for interacting with everyday objects. The tightly integrated sensing elements within the 3D printed structures, as presented herein, can pave the way for a new generation of truly smart material systems that can possibly change their appearance and shape autonomously.
- Subjects :
- lcsh:Computer engineering. Computer hardware
Materials science
Inkwell
Capacitive sensing
lcsh:Control engineering systems. Automatic machinery (General)
Soft robotics
Mechanical engineering
lcsh:TK7885-7895
intrinsic sensing
Smart material
Pressure sensor
multimaterial 3D printing
lcsh:TJ212-225
Thermoplastic polyurethane
capacitive sensors
robotic hands
material integrated sensing
Conductive ink
additive manufacturing
General Economics, Econometrics and Finance
Electrical conductor
Subjects
Details
- ISSN :
- 26404567
- Volume :
- 2
- Database :
- OpenAIRE
- Journal :
- Advanced Intelligent Systems
- Accession number :
- edsair.doi.dedup.....35d318539ae505f055a1304b791acfa7