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A Sense of Touch for the Shadow Modular Grasper

Research output: Contribution to journalArticle

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A Sense of Touch for the Shadow Modular Grasper. / Pestell, Nicholas; Cramphorn, Luke; Lepora, Nathan; Papadopoulos, Fotios.

In: IEEE Robotics and Automation Letters, Vol. 4, No. 2, 8656557, 01.04.2019, p. 2220-2226.

Research output: Contribution to journalArticle

Harvard

Pestell, N, Cramphorn, L, Lepora, N & Papadopoulos, F 2019, 'A Sense of Touch for the Shadow Modular Grasper', IEEE Robotics and Automation Letters, vol. 4, no. 2, 8656557, pp. 2220-2226. https://doi.org/10.1109/LRA.2019.2902434

APA

Pestell, N., Cramphorn, L., Lepora, N., & Papadopoulos, F. (2019). A Sense of Touch for the Shadow Modular Grasper. IEEE Robotics and Automation Letters, 4(2), 2220-2226. [8656557]. https://doi.org/10.1109/LRA.2019.2902434

Vancouver

Pestell N, Cramphorn L, Lepora N, Papadopoulos F. A Sense of Touch for the Shadow Modular Grasper. IEEE Robotics and Automation Letters. 2019 Apr 1;4(2):2220-2226. 8656557. https://doi.org/10.1109/LRA.2019.2902434

Author

Pestell, Nicholas ; Cramphorn, Luke ; Lepora, Nathan ; Papadopoulos, Fotios. / A Sense of Touch for the Shadow Modular Grasper. In: IEEE Robotics and Automation Letters. 2019 ; Vol. 4, No. 2. pp. 2220-2226.

Bibtex

@article{f001861b1e4a4679bbeeefdc3ab42d44,
title = "A Sense of Touch for the Shadow Modular Grasper",
abstract = "In this letter, we have designed and built a set of tactile fingertips for integration with a commercial three-fingered robot hand, the Shadow Modular Grasper. The fingertips are an evolution of an established optical biomimetic tactile sensor, the TacTip. In developing the tactile fingertips, we have progressed the technology in areas such as miniaturization, development of custom-shaped finger-pads, and integration of multiple sensors. From these fingertips, we extract a set of high-level features with intuitive relationships to tactile quantities such as contact location and pressure. We present a simple linear-regression method for predicting roll and pitch of the finger-pad relative to a surface normal and show that the method generalizes to unknown depths and shapes. Finally, we apply this prediction to a grasp-control method with the Modular Grasper and show that it can adjust the grasp on three real-world objects from the YCB object set in order to attain a greater area of contact at each fingertip.",
keywords = "Force and tactile sensing, grasping, perception for grasping and manipulation, biomimetics",
author = "Nicholas Pestell and Luke Cramphorn and Nathan Lepora and Fotios Papadopoulos",
year = "2019",
month = "4",
day = "1",
doi = "10.1109/LRA.2019.2902434",
language = "English",
volume = "4",
pages = "2220--2226",
journal = "IEEE Robotics and Automation Letters",
issn = "2377-3766",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
number = "2",

}

RIS - suitable for import to EndNote

TY - JOUR

T1 - A Sense of Touch for the Shadow Modular Grasper

AU - Pestell, Nicholas

AU - Cramphorn, Luke

AU - Lepora, Nathan

AU - Papadopoulos, Fotios

PY - 2019/4/1

Y1 - 2019/4/1

N2 - In this letter, we have designed and built a set of tactile fingertips for integration with a commercial three-fingered robot hand, the Shadow Modular Grasper. The fingertips are an evolution of an established optical biomimetic tactile sensor, the TacTip. In developing the tactile fingertips, we have progressed the technology in areas such as miniaturization, development of custom-shaped finger-pads, and integration of multiple sensors. From these fingertips, we extract a set of high-level features with intuitive relationships to tactile quantities such as contact location and pressure. We present a simple linear-regression method for predicting roll and pitch of the finger-pad relative to a surface normal and show that the method generalizes to unknown depths and shapes. Finally, we apply this prediction to a grasp-control method with the Modular Grasper and show that it can adjust the grasp on three real-world objects from the YCB object set in order to attain a greater area of contact at each fingertip.

AB - In this letter, we have designed and built a set of tactile fingertips for integration with a commercial three-fingered robot hand, the Shadow Modular Grasper. The fingertips are an evolution of an established optical biomimetic tactile sensor, the TacTip. In developing the tactile fingertips, we have progressed the technology in areas such as miniaturization, development of custom-shaped finger-pads, and integration of multiple sensors. From these fingertips, we extract a set of high-level features with intuitive relationships to tactile quantities such as contact location and pressure. We present a simple linear-regression method for predicting roll and pitch of the finger-pad relative to a surface normal and show that the method generalizes to unknown depths and shapes. Finally, we apply this prediction to a grasp-control method with the Modular Grasper and show that it can adjust the grasp on three real-world objects from the YCB object set in order to attain a greater area of contact at each fingertip.

KW - Force and tactile sensing

KW - grasping

KW - perception for grasping and manipulation

KW - biomimetics

UR - http://www.scopus.com/inward/record.url?scp=85063031176&partnerID=8YFLogxK

U2 - 10.1109/LRA.2019.2902434

DO - 10.1109/LRA.2019.2902434

M3 - Article

VL - 4

SP - 2220

EP - 2226

JO - IEEE Robotics and Automation Letters

JF - IEEE Robotics and Automation Letters

SN - 2377-3766

IS - 2

M1 - 8656557

ER -