A New Silicone Structure for uSkin—A Soft, Distributed, Digital 3-Axis Skin Sensor and Its Integration on the Humanoid Robot iCub

Tomo, Tito Pradhono; Regoli, Massimo; Schmitz, Alexander; Natale, Lorenzo; Kristanto, Harris; Somlor, Sophon; Jamone, Lorenzo; Metta, Giorgio; Sugano, Shigeki

doi:10.1109/lra.2018.2812915

Cited by 101 publications

(61 citation statements)

References 22 publications

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“…The robot behaviors are defined by a specific selection of controllers with a specific control fusion method. For example, the skin-compliance behavior is composed of a joint task, a gravity compensation task, and the skin task, fused with the method defined in (18). This behavior transforms a stiff industrial robot into a fully compliant robot.…”

Section: (A) Pipeline Of Our General Control Framework the Framewomentioning

confidence: 99%

“…RoboSkin has been used to cover a Nao robot with 200 force sensors and an iCub with 2000 force sensors [16], [17]. More recently, there has been progress in upgrading Robot-Skin with 3-D magnetic force sensors [18], [19]. A useful large-scale deployment of the robot skin needs to address the efficient transmission, organization, and representation of tactile information.…”

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A Comprehensive Realization of Robot Skin: Sensors, Sensing, Control, and Applications

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Section: (A) Pipeline Of Our General Control Framework the Framewomentioning

confidence: 99%

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confidence: 99%

A Comprehensive Realization of Robot Skin: Sensors, Sensing, Control, and Applications

et al. 2019

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“…In the SAMI architecture, the sense function is independent of the type of sensors which could be multi-modal and thus could take information based on the input from any of the five Aristotelian methods of perception known as the five senses, namely, the sight [23], [24], the hearing [25], [26], the touch [27], [28], the smell [29], and the taste [30].…”

Section: Proposed Robot Architecturementioning

confidence: 99%

SAMI: Interactive, Multi-Sense Robot Architecture

Calzado

Lindsay

Chen

et al. 2018

2018 IEEE 22nd International Conference on Intelligent Engineering Systems (INES)

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The design and development of robotic agents to be deployed in the real world for human-robot interaction (HRI) purpose require adequate robot architecture. In this paper, we present a new, middle-out robot architecture which extends the reactive paradigm by adding an interactive layer, leading to the Sense-Act-Modulated-by-Interactions (SAMI) architecture. This proposed SAMI robot architecture has been embodied by a mobile, multi-modal, SAMI-based robot and successfully validated by carrying out tests of the SAMI embodiment in real-world, unstructured environment.

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“…Previously established relationships between conductivity and applied pressure, damping properties and external field, and shear modulus and external field, make them valuable for sensing and actuation . Recent approaches to magnetic tactile sensing measure magnetic flux with arrays of Hall effect sensors and rigid permanent magnets embedded within an elastomer . Magnetic flux can also be measured through inductance changes with giant magneto‐impedance materials .…”

Section: Introductionmentioning

confidence: 99%

Soft Magnetic Skin for Continuous Deformation Sensing

Hellebrekers

Kroemer

Majidi

2019

Advanced Intelligent Systems

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Recent progress in soft-matter sensors has shown improved fabrication techniques, resolution, and range. However, scaling up these sensors into an information-rich tactile skin remains largely limited by designs that require a corresponding increase in the number of wires to support each new sensing node. To address this, a soft tactile skin that can estimate force and localize contact over a continuous 15 mm 2 area with a single integrated circuit and four output wires is introduced. The skin is composed of silicone elastomer loaded with randomly distributed magnetic microparticles. Upon deformation, the magnetic particles change position and orientation with respect to an embedded magnetometer, resulting in a change in the net measured magnetic field. Two experiments are reported to calibrate and estimate both location and force of surface contact. The classification algorithms can localize pressure with an accuracy of >98% on both grid and circle pattern. Regression algorithms can localize pressure to a 3 mm 2 area on average. This proof-of-concept sensing skin addresses the increasing need for a simple-to-fabricate, quick-to-integrate, and information-rich tactile surface for use in robotic manipulation, soft systems, and biomonitoring.

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A New Silicone Structure for uSkin—A Soft, Distributed, Digital 3-Axis Skin Sensor and Its Integration on the Humanoid Robot iCub

Cited by 101 publications

References 22 publications

A Comprehensive Realization of Robot Skin: Sensors, Sensing, Control, and Applications

A Comprehensive Realization of Robot Skin: Sensors, Sensing, Control, and Applications

SAMI: Interactive, Multi-Sense Robot Architecture

Soft Magnetic Skin for Continuous Deformation Sensing

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