Jörg Conradt

Principal Investigator


EECS, CST

KTH Royal Institute of Technology, Sweden

Lindstedtsvägen 5
114 28 Stockholm, Sweden



A Miniaturised Neuromorphic Tactile Sensor integrated with an Anthropomorphic Robot Hand


Journal article


Benjamin Ward-Cherrier, J. Conradt, M. Catalano, M. Bianchi, N. Lepora
IEEE/RJS International Conference on Intelligent RObots and Systems, 2020

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APA   Click to copy
Ward-Cherrier, B., Conradt, J., Catalano, M., Bianchi, M., & Lepora, N. (2020). A Miniaturised Neuromorphic Tactile Sensor integrated with an Anthropomorphic Robot Hand. IEEE/RJS International Conference on Intelligent RObots and Systems.


Chicago/Turabian   Click to copy
Ward-Cherrier, Benjamin, J. Conradt, M. Catalano, M. Bianchi, and N. Lepora. “A Miniaturised Neuromorphic Tactile Sensor Integrated with an Anthropomorphic Robot Hand.” IEEE/RJS International Conference on Intelligent RObots and Systems (2020).


MLA   Click to copy
Ward-Cherrier, Benjamin, et al. “A Miniaturised Neuromorphic Tactile Sensor Integrated with an Anthropomorphic Robot Hand.” IEEE/RJS International Conference on Intelligent RObots and Systems, 2020.


BibTeX   Click to copy

@article{benjamin2020a,
  title = {A Miniaturised Neuromorphic Tactile Sensor integrated with an Anthropomorphic Robot Hand},
  year = {2020},
  journal = {IEEE/RJS International Conference on Intelligent RObots and Systems},
  author = {Ward-Cherrier, Benjamin and Conradt, J. and Catalano, M. and Bianchi, M. and Lepora, N.}
}

Abstract

Restoring tactile sensation is essential to enable in-hand manipulation and the smooth, natural control of upper-limb prosthetic devices. Here we present a platform to contribute to that long-term vision, combining an anthropomorphic robot hand (QB SoftHand) with a neuromorphic optical tactile sensor (neuroTac). Neuromorphic sensors aim to produce efficient, spike-based representations of information for bio-inspired processing. The development of this 5-fingered, sensorized hardware platform is validated with a customized mount allowing manual control of the hand. The platform is demonstrated to succesfully identify 4 objects from the YCB object set, and accurately discriminate between 4 directions of shear during stable grasps. This platform could lead to wide-ranging developments in the areas of haptics, prosthetics and telerobotics.


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