Projekt

Neuromorphic Sensing with Active Efficient Coding for Edge Computing (SNACE) Edge-computing applications (e.g., medical devices, wearable electronics, or mobile robotic platforms) typically require processing various sensory signals with constrained computing power. The current state-of-the-art technology in Integrated Circuits (ICs) has already witnessed tremendous progress towards more energy-efficient solutions for edge computing, with higher scores achieved with neuromorphic mixed-signal and analog subthreshold architectures at large scales. However, efficient deployment of such systems in real-world scenarios imposes the need for more robust and reliable front-end designs that can cope with external noise and device variability. As proposed by the Active Efficient Coding (AEC) theory, it appears that biological systems have learned to cope with finite computational resources and environment complexity by compensating with adaptive behavior. Hence, if applied to edge computing, such principles promise to solve current roadblocks towards truly efficient sensory systems on the edge. Thus, the goal of this project is to unleash the potential of extreme-edge computing by leveraging the principles of AEC for efficient near/in-sensor modulation. We will provide a framework for designing and characterizing a novel generation of Adaptive Neuromorphic Sensory (ANS) systems that can jointly extract sensory information from multiple sources while modulating sensor transduction. Upon quantitative assessment of the ACE theory applied to embedded systems, we propose to deliver and validate an example ANS system in a real-world scenario.

• Dr.-Ing. René Schuster

  Rheinland-Pfälzische Technische
  Universität Kaiserslautern-Landau (RPTU)
  Computer Science
  Augmented Vision
  Kaiserslautern
  

• Dr. Siao Wang, Ph.D.

  Italian Institute of Technology (IIT)
  Center for Robotics and Intelligent Systems
  Event Driven Perception for Robotics
  Genova
  Italien
  

• Lea Steffen

  FZI Forschungszentrum Informatik
  am Karlsruher Institut für Technologie
  Interaktive Diagnose- und Servicesysteme
  Karlsruhe
  

• Dr. Nicoletta Risi, Ph.D

  University of Groningen
  Faculty of Science and Engineering
  Zernike Institute for Advanced Materials
  Groningen
  Niederlande
  

• Dr. Claudia Lenk

  Technische Universität Ilmenau
  Fakultät Elektro- und Informationstechnik
  Institut für Mikro- und Nano-Elektronik
  Ilmenau