Self healable neuromorphic memtransistor elements for decentralized sensory signal processing in robotics
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Published:2020-08-12
Issue:1
Volume:11
Page:
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ISSN:2041-1723
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Container-title:Nature Communications
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language:en
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Short-container-title:Nat Commun
Author:
John Rohit AbrahamORCID, Tiwari Naveen, Patdillah Muhammad Iszaki Bin, Kulkarni Mohit Rameshchandra, Tiwari Nidhi, Basu JoydeepORCID, Bose Sumon KumarORCID, Ankit ORCID, Yu Chan Jun, Nirmal Amoolya, Vishwanath Sujaya Kumar, Bartolozzi ChiaraORCID, Basu ArindamORCID, Mathews NripanORCID
Abstract
AbstractSensory information processing in robot skins currently rely on a centralized approach where signal transduction (on the body) is separated from centralized computation and decision-making, requiring the transfer of large amounts of data from periphery to central processors, at the cost of wiring, latency, fault tolerance and robustness. We envision a decentralized approach where intelligence is embedded in the sensing nodes, using a unique neuromorphic methodology to extract relevant information in robotic skins. Here we specifically address pain perception and the association of nociception with tactile perception to trigger the escape reflex in a sensorized robotic arm. The proposed system comprises self-healable materials and memtransistors as enabling technologies for the implementation of neuromorphic nociceptors, spiking local associative learning and communication. Configuring memtransistors as gated-threshold and -memristive switches, the demonstrated system features in-memory edge computing with minimal hardware circuitry and wiring, and enhanced fault tolerance and robustness.
Publisher
Springer Science and Business Media LLC
Subject
General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry
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