Self healable neuromorphic memtransistor elements for decentralized sensory signal processing in robotics

Rohit Abraham John, Naveen Tiwari, Muhammad Iszaki Bin Patdillah, Mohit Rameshchandra Kulkarni, Nidhi Tiwari, Joydeep Basu, Sumon Kumar Bose, Ankit, Chan Jun Yu, Amoolya Nirmal, Sujaya Kumar Vishwanath, Chiara Bartolozzi, Arindam Basu () and Nripan Mathews ()
Additional contact information
Rohit Abraham John: Nanyang Technological University
Naveen Tiwari: Nanyang Technological University
Muhammad Iszaki Bin Patdillah: Nanyang Technological University
Mohit Rameshchandra Kulkarni: Nanyang Technological University
Nidhi Tiwari: Nanyang Technological University
Joydeep Basu: Nanyang Technological University
Sumon Kumar Bose: Nanyang Technological University
Ankit: Nanyang Technological University
Chan Jun Yu: Nanyang Technological University
Amoolya Nirmal: Nanyang Technological University
Sujaya Kumar Vishwanath: Nanyang Technological University
Chiara Bartolozzi: Italian Institute of Technology
Arindam Basu: Nanyang Technological University
Nripan Mathews: Nanyang Technological University

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: Abstract Sensory 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.

Date: 2020
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DOI: 10.1038/s41467-020-17870-6

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