Published June 8, 2022 | Version v1
Journal article Open

Neuro-inspired electronic skin for robots

  • 1. University of Glasgow
  • 2. Neuromorphic Computing Intel Labs, Munich, Germany.
  • 3. Department of Research, New Technologies, Innovation, BMW Group, Parkring 19, 85748 Garching bei Munchen, Germany & Cognitive Robotics and Tactile Intelligence Group, Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, Netherlands

Description

Touch is a complex sensing modality owing to large number of receptors (mechano, thermal, pain) nonuniformly embedded in the soft skin all over the body. These receptors can gather and encode the large tactile data, allowing us to feel and perceive the real world. This efficient somatosensation far outperforms the touch-sensing capability of most of the state-of-the-art robots today and suggests the need for neural-like hardware for electronic skin (e-skin). This could be attained through either innovative schemes for developing distributed electronics or repurposing the neuromorphic circuits developed for other sensory modalities such as vision and audio. This Review highlights the hardware implementations of various computational building blocks for e-skin and the ways they can be integrated to potentially realize human skin–like or peripheral nervous system–like functionalities. The neural-like sensing and data processing are discussed along with various algorithms and hardware architectures. The integration of ultrathin neuromorphic chips for local computation and the printed electronics on soft substrate used for the development of e-skin over large areas are expected to advance robotic interaction as well as open new avenues for research in medical instrumentation, wearables, electronics, and neuroprosthetics.

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Additional details

Funding

Engineering Fellowship for Growth - Neuromorphic Printed Tactile Skin (NeuPRINTSKIN) (Ext) EP/R029644/1
UK Research and Innovation
'Hetero-print': A holistic approach to transfer-printing for heterogeneous integration in manufacturing EP/R03480X/1
UK Research and Innovation