Presentation + Paper
16 May 2017 Characterization of large-area pressure sensitive robot skin
Mohammad Nasser Saadatzi, Joshua R. Baptist, Indika B. Wijayasinghe, Dan O. Popa
Author Affiliations +
Abstract
Sensorized robot skin has considerable promise to enhance robots’ tactile perception of surrounding environments. For physical human-robot interaction (pHRI) or autonomous manipulation, a high spatial sensor density is required, typically driven by the skin location on the robot. In our previous study, a 4x4 flexible array of strain sensors were printed and packaged onto Kapton sheets and silicone encapsulants. In this paper, we are extending the surface area of the patch to larger arrays with up to 128 tactel elements. To address scalability, sensitivity, and calibration challenges, a novel electronic module, free of the traditional signal conditioning circuitry was created. The electronic design relies on a software-based calibration scheme using high-resolution analog-to-digital converters with internal programmable gain amplifiers. In this paper, we first show the efficacy of the proposed method with a 4x4 skin array using controlled pressure tests, and then perform procedures to evaluate each sensor’s characteristics such as dynamic force-to-strain property, repeatability, and signal-to-noise-ratio. In order to handle larger sensor surfaces, an automated force-controlled test cycle was carried out. Results demonstrate that our approach leads to reliable and efficient methods for extracting tactile models for use in future interaction with collaborative robots.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mohammad Nasser Saadatzi, Joshua R. Baptist, Indika B. Wijayasinghe, and Dan O. Popa "Characterization of large-area pressure sensitive robot skin", Proc. SPIE 10216, Smart Biomedical and Physiological Sensor Technology XIV, 102160G (16 May 2017); https://doi.org/10.1117/12.2262821
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Sensors

Skin

Signal to noise ratio

Data acquisition

Electronic circuits

LabVIEW

Amplifiers

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