Organic Piezoresistive Pressure Sensitive Robotic Skin for Physical Human-Robot Interaction

Wei, Danming; Zhang, Ruoshi; Saadatzi, Mohammad Nasser; Olowo, Olalekan O; Popa, Dan O.

doi:10.1115/1.0001902v

Cited by 4 publications

(8 citation statements)

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“…An illustration of the EHD system is provided in Figure 5(C) [147]. EHD printing is affects strongly by a wide range of printing and ink parameters, which must be optimized in tandem to produce a quality deposition [44,[148][149][150][151][152][153][154].…”

Section: E Electrohydrodynamic Printingmentioning

confidence: 99%

“…For instance, the ink's surface tension, viscosity, and dielectric nature in addition to the printer's substrate offset height, electric potential distribution, nozzle width and length and flow rate are all essential parameters. As a result, stringent requirements are placed on the ink synthesis [44,[148][149][150][151][152][153][154]. These inks must have low surface tensions (<50 mN/m) and high viscosities (1-10 Pa S), although increasing both parameters tend to cause print smearing after deposition and reduce resolution [150,152].…”

Section: Emerging Topicsmentioning

confidence: 99%

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Printed Strain Sensors for Motion Recognition: A Review of Materials, Fabrication Methods, and Machine Learning Algorithms

Zavanelli,

Kwon,

Yeo

2024

IEEE Open J. Eng. Med. Biol.

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Recent studies in functional nanomaterials with advanced macro, micro, and nano-scale structures have yielded substantial improvements in human-interfaced strain sensors for motion and gesture recognition. Furthermore, fundamental advances in nanomaterial printing have been developed and leveraged to translate these materials and mechanical innovations into practical applications. Significant progress in machine learning for human-interfaced strain sensing has unlocked numerous opportunities to improve lives and the human experience through healthcare innovations, sports performance monitoring, and human-machine interfaces. However, several key challenges still must be overcome if strain sensors are to become ubiquitous tools for human motion recognition. This review begins with a summary of the critical strain-sensing mechanisms employed today and how recent works have sought to push their boundaries. It then proceeds to cover the primary functional materials used in wearable strain sensors from a performance and printability perspective. Next is a review of recent advances in nanomaterial printing to produce the complex structures necessary for functional devices. Next, we summarize machine learning approaches for human gesture recognition and the myriad applications and use cases for human-interfaced strain sensors. Finally, it concludes with a discussion of challenges and opportunities for future research in the field.

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Section: E Electrohydrodynamic Printingmentioning

confidence: 99%

Section: Emerging Topicsmentioning

confidence: 99%

Printed Strain Sensors for Motion Recognition: A Review of Materials, Fabrication Methods, and Machine Learning Algorithms

Zavanelli,

Kwon,

Yeo

2024

IEEE Open J. Eng. Med. Biol.

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“…In previous work [9][10][11], we fabricated and laminated double-layer sensor arrays with two same IDE strain gauge structures. The sensors were coated PEDOT: PSS to compensate for temperature drift and enhance force reaction performance.…”

Section: B Skin Tactile Sensor Designmentioning

confidence: 99%

“…Later, we developed the fabrication process of the IDE structure of the SkinCell sensor using MEMS fabrication techniques in the cleanroom [9]. To improve the sensitivity and compensate for the temperature drift, we fabricated double-layer sensor arrays with a lamination process [10,11]. The parametric investigation of the double-layer sensor array is documented in [12].…”

Section: Introductionmentioning

confidence: 99%

“…The parametric investigation of the double-layer sensor array is documented in [12]. On the top of the IDEs, a conductive organic piezoresistive material of poly (3,4-ethylene dioxythiophene) polystyrene sulfonate or PEDOT: PSS was applied as the active tactile sensing agent [10,11]. However, due to the complexity of the cleanroom fabrication process of the SkinCell sensors, the reliability of the sensors and the fabrication yield were not satisfactory.…”

Section: Introductionmentioning

confidence: 99%

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Precise Fabrication of Tactile Sensors using a Custom Additive Manufacturing Platform

Wei

Zhang

Lin

et al. 2023

Preprint

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This paper presents the NeXus, a precision robotic platform with additive manufacturing capabilities that can be used to prototype strain gauge-based tactile sensors – SkinCells - on flexible substrates. An Aerosol Inkjet printer was employed to print the strain gauge structures of the SkinCell sensor. The design of this sensor combines curvilinear geometries representing both a radial shape structure and an arc shape structure, which have opposite gauge responses when the force is applied to the center of the sensor. The fabrication process of the SkinCell sensor is predicated on a parametric kinematic calibration of the NeXus to identify features on the sensor substrate and align them to the printing and metrology tools. Several strain gauge SkinCell sensor samples were printed on pre-fabricated flexible substrates using the NeXus. Results indicate a calibration precision of approximately 36 microns with 100 microns line-width features. This precision is sufficient to ensure that all printed gauges are electrically connected to the prefabricated contacts. Furthermore, the printing errors accumulating during a continuous four-sensor array print also fall within the contact tolerance.

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Precision evaluation of tactile sensor fabrication using a robotic additive manufacturing platform

Wei,

Zhang,

Lin

et al. 2024

J Micro-Bio Robot

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Organic Piezoresistive Pressure Sensitive Robotic Skin for Physical Human-Robot Interaction

Cited by 4 publications

References 0 publications

Printed Strain Sensors for Motion Recognition: A Review of Materials, Fabrication Methods, and Machine Learning Algorithms

Printed Strain Sensors for Motion Recognition: A Review of Materials, Fabrication Methods, and Machine Learning Algorithms

Precise Fabrication of Tactile Sensors using a Custom Additive Manufacturing Platform

Precision evaluation of tactile sensor fabrication using a robotic additive manufacturing platform

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