Soft Radio-Frequency Identification Sensors: Wireless Long-Range Strain Sensors Using Radio-Frequency Identification.
RFID
antenna
passive
soft sensing
wireless
Journal
Soft robotics
ISSN: 2169-5180
Titre abrégé: Soft Robot
Pays: United States
ID NLM: 101623819
Informations de publication
Date de publication:
02 2019
02 2019
Historique:
pubmed:
9
11
2018
medline:
9
11
2018
entrez:
9
11
2018
Statut:
ppublish
Résumé
Increasing amounts of attention are being paid to the study of Soft Sensors and Soft Systems. Soft Robotic Systems require input from advances in the field of Soft Sensors. Soft sensors can help a soft robot to perceive and to act upon its immediate environment. The concept of integrating sensing capabilities into soft robotic systems is becoming increasingly important. One challenge is that most of the existing soft sensors have a requirement to be hardwired to power supplies or external data processing equipment. This requirement hinders the ability of a system designer to integrate soft sensors into soft robotic systems. In this article, we design, fabricate, and characterize a new soft sensor, which benefits from a combination of radio-frequency identification (RFID) tag design and microfluidic sensor fabrication technologies. We designed this sensor using the working principle of an RFID transporter antenna, but one whose resonant frequency changes in response to an applied strain. This new microfluidic sensor is intrinsically stretchable and can be reversibly strained. This sensor is a passive and wireless device, and as such, it does not require a power supply and is capable of transporting data without a wired connection. This strain sensor is best understood as an RFID tag antenna; it shows a resonant frequency change from approximately 860 to 800 MHz upon an applied strain change from 0% to 50%. Within the operating frequency, the sensor shows a standoff reading range of >7.5 m (at the resonant frequency). We characterize, experimentally, the electrical performance and the reliability of the fabrication process. We demonstrate a pneumatic soft robot that has four microfluidic sensors embedded in four of its legs, and we describe the implementation circuit to show that we can obtain movement information from the soft robot using our wireless soft sensors.
Identifiants
pubmed: 30407119
doi: 10.1089/soro.2018.0026
pmc: PMC6386780
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
82-94Références
Adv Mater. 2013 May 28;25(20):2773-8
pubmed: 23440975
Adv Mater. 2010 Jul 6;22(25):2749-52
pubmed: 20414886
Nature. 2016 Aug 24;536(7617):451-5
pubmed: 27558065
Soft Robot. 2015 Mar 1;2(1):7-25
pubmed: 27625913
Proc Natl Acad Sci U S A. 2011 Dec 20;108(51):20400-3
pubmed: 22123978
Angew Chem Int Ed Engl. 2011 Feb 18;50(8):1890-5
pubmed: 21328664
Lab Chip. 2014 Nov 7;14(21):4205-12
pubmed: 25144304
Sci Transl Med. 2016 May 4;8(337):337ra64
pubmed: 27147588
Langmuir. 2013 May 21;29(20):6194-200
pubmed: 23659455
Science. 2015 Jul 10;349(6244):161-5
pubmed: 26160940
Small. 2015 Feb 25;11(8):906-12
pubmed: 25367846
Lab Chip. 2012 Aug 21;12(16):2782-91
pubmed: 22711057
Annu Rev Biomed Eng. 2012;14:113-28
pubmed: 22524391