State-of-the-art tactile sensing arrays are not scalable to large numbers of sensing units due to their raster-scanned process. This interface process results in a high degree of wiring complexity and a tradeoff between spatial and temporal resolution. In this paper, we present a new neuromimetic tactile sensing scheme that allows for single-wire signal transduction and asynchronous signal transmission - without the incorporation of electronics into each sensing element. A prototype device with spatial frequency encoding was developed using flexible fabric-based e-textile materials, and the ability of this new sensing scheme was demonstrated through a texture discrimination task. Overall, the neuromimetic spatial frequency encoded sensor array had comparable performance to the state-of-the-art tactile sensor array and achieved a classification accuracy of 86.58%. Future tactile sensing systems and electronic skins can emulate the spatial frequency encoding architecture presented here to become dense and numerous while retaining excellent temporal resolution.
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Towards scalable soft e-skin: Flexible event-based tactile-sensors using wireless sensor elements embedded in soft elastomer
Scalable, high-density electronic skins (e-skins) are a desirable goal of tactile sensing. However, a realization of this goal has been elusive due to the trade-off between spatial and temporal resolution that current tactile sensors suffer from.
Additionally, as tactile sensing grids become large, wiring becomes unmanageable, and there is a need for a wireless approach. In this work, a scalable, event-based, passive tactilesensing system is proposed that is based on radio-frequency
identification (RFID) technology. An RFID-based tactile sensing hand is developed with 19 pressure sensing taxels. The taxels are read wirelessly using a single ‘hand-shaped’ RFID antenna. Each RFID tag is transformed into a pressure sensor by disconnecting the RFID chip from its antenna and embedding the chip and antenna into soft elastomer with an air gap introduced between the RFID chip and its antenna. When a pressure event occurs, the RFID chip contacts its antenna and
receives power and communicates with the RFID reader. Thus, the sensor is transformed into a biomimetic event-based sensor, whose response is activated only when used. Further, this work demonstrates the feasibility of constructing event-based, passive sensing grids that can be read wirelessly. Future tactile sensing e-skins can utilize this approach to become scalable and dense,
while retaining high temporal resolution. Moreover, this approach can be applied beyond tactile sensing, for the development of scalable and high-density sensors of any modality.
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- Award ID(s):
- 1849417
- NSF-PAR ID:
- 10283657
- Date Published:
- Journal Name:
- IEEE BIOROB Conference
- Page Range / eLocation ID:
- 334 to 339
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Wearable piezoresistive sensors are being developed as electronic skins (E‐skin) for broad applications in human physiological monitoring and soft robotics. Tactile sensors with sufficient sensitivities, durability, and large dynamic ranges are required to replicate this critical component of the somatosensory system. Multiple micro/nanostructures, materials, and sensing modalities have been reported to address this need. However, a trade‐off arises between device performance and device complexity. Inspired by the microstructure of the spinosum at the dermo epidermal junction in skin, a low‐cost, scalable, and high‐performance piezoresistive sensor is developed with high sensitivity (0.144 kPa‐1), extensive sensing range ( 0.1–15 kPa), fast response time (less than 150 ms), and excellent long‐term stability (over 1000 cycles). Furthermore, the piezoresistive functionality of the device is realized via a flexible transparent electrode (FTE) using a highly stable reduced graphene oxide self‐wrapped copper nanowire network. The developed nanowire‐based spinosum microstructured FTEs are amenable to wearable electronics applications.
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Madden, John D. ; Anderson, Iain A. ; Shea, Herbert R. (Ed.)Ras Labs makes Synthetic Muscle™, which is a class of electroactive polymer (EAP) based materials and actuators that sense pressure (gentle touch to high impact), controllably contract and expand at low voltage (1.5 V to 50 V, including use of batteries), and attenuate force. We are in the robotics era, but robots do have their challenges. Currently, robotic sensing is mainly visual, which is useful up until the point of contact. To understand how an object is being gripped, tactile feedback is needed. For handling fragile objects, if the grip is too tight, breakage occurs, and if the grip is too loose, the object will slip out of the grasp, also leading to breakage. Rigid robotic grippers using a visual feedback loop can struggle to determine the exact point and quality of contact. Robotic grippers can also get a stuttering effect in the visual feedback loop. By using soft Synthetic Muscle™ based EAP pads as the sensors, immediate feedback was generated at the first point of contact. Because these pads provided a soft, compliant interface, the first point of contact did not apply excessive force, allowing the force applied to the object to be controlled. The EAP sensor could also detect a change in pressure location on its surface, making it possible to detect and prevent slippage by then adjusting the grip strength. In other words, directional glide provided feedback for the presence of possible slippage to then be able to control a slightly tighter grip, without stutter, due to both the feedback and the soft gentleness of the fingertip-like EAP pads themselves. The soft nature of the EAP fingertip pad also naturally held the gripped object, improving the gripping quality over rigid grippers without an increase in applied force. Analogous to finger-like tactile touch, the EAPs with appropriate coatings and electronics were positioned as pressure sensors in the fingertip or end effector regions of robotic grippers. This development of using Synthetic Muscle™ based EAPs as soft sensors provided for sensors that feel like the pads of human fingertips. Basic pressure position and magnitude tests have been successful, with pressure sensitivity down to 0.05 N. Most automation and robots are very strong, very fast, and usually need to be partitioned away from humans for safety reasons. For many repetitive tasks that humans do with delicate or fragile objects, it would be beneficial to use robotics; whether it is for agriculture, medical surgery, therapeutic or personal care, or in extreme environments where humans cannot enter, including with contagions that have no cure. Synthetic Muscle™ was also retrofitted as actuator systems into off-the-shelf robotic grippers and is being considered in novel biomimetic gripper designs, operating at low voltages (less than 50 V). This offers biomimetic movement by contracting like human muscles, but also exceeds natural biological capabilities by expanding under reversed electric polarity. Human grasp is gentle yet firm, with tactile touch feedback. In conjunction with shape-morphing abilities, these EAPs also are being explored to intrinsically sense pressure due to the correlation between mechanical force applied to the EAP and its electronic signature. The robotic field is experiencing phenomenal growth in this fourth phase of the industrial revolution, the robotics era. The combination of Ras Labs’ EAP shape-morphing and sensing features promises the potential for robotic grippers with human hand-like control and tactile sensing. This work is expected to advance both robotics and prosthetics, particularly for collaborative robotics to allow humans and robots to intuitively work safely and effectively together.more » « less
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null (Ed.)Passive radio-frequency identification (RFID) tags are attractive because they are low cost, battery-free, and easy to deploy. This technology is traditionally being used to identify tags attached to the objects. In this paper, we explore the feasibility of turning passive RFID tags into battery-free temperature sensors. The impedance of the RFID tag changes with the temperature and this change will be manifested in the reflected signal from the tag. This opens up an opportunity to realize battery-free temperature sensing using a passive RFID tag with already deployed Commercial Off-the-Shelf (COTS) RFID reader-antenna infrastructure in supply chain management or inventory tracking. However, it is challenging to achieve high accuracy and robustness against the changes in the environment. To address these challenges, we first develop a detailed analytical model to capture the impact of temperature change on the tag impedance and the resulting phase of the reflected signal. We then build a system that uses a pair of tags, which respond differently to the temperature change to cancel out other environmental impacts. Using extensive evaluation, we show our model is accurate and our system can estimate the temperature within a 2.9 degree centigrade median error and support a normal read range of 3.5 m in an environment-independent manner.more » « less
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Currently, there is an increasing interest in the use of RFID systems with passive or battery-less tags with sensors incorporated, also known as computational RFID (CRFID) systems. These passive tags use the reader signal to power up their microcontroller and an attached sensor. Following the current standard EPC C1G2, the reader must identify the tag (receive the tag's identification code) prior to receive data from its sensor. In a typical RFID scenario, several sensor tags share the reader interrogation zone, and during their identification process, their responses often collide, increasing their identification time. Therefore, RFID application developers must be mindful of tag anti-collision protocols when dealing with CRFID tags in dense RFID sensor networks. So far, significant effort has been invested in simulation-based analysis of the performance of anti-collision protocols regarding the tags identification time. However, no one has explored the experimental performance of anti-collision protocols in an RFID sensor network using CRFID. This paper: (i) demonstrates that the impact of one tag identification time over the total time required to read one sensor data from that same tag is very significant, and (ii) presents an UHF-SDR RFID system which validates the improvement of FuzzyQ, a fast anticollision protocol, in relation to the protocol used in the current RFID standard.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/BioRob49111.2020.9224353
