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Spiking Elementary Motion Detector in Neuromorphic Systems.

M B Milde1, O J N Bertrand2, H Ramachandran3

  • 1Institute of Neuroinformatics, University of Zurich, and ETH Zurich, 8057 Zurich, Switzerland mmilde@ini.uzh.ch.

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Researchers developed a novel spiking elementary motion detector (sEMD) using event-based vision sensors for fast collision avoidance in robots. This new circuit efficiently estimates time-to-travel, crucial for navigating cluttered environments.

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Area of Science:

  • Robotics and Neuromorphic Engineering
  • Computer Vision
  • Biologically Inspired Computing

Background:

  • Optic flow from apparent motion aids navigation and obstacle avoidance.
  • Conventional frame-based optic flow estimation faces hardware limitations for small, fast agents.
  • Event-based vision sensors offer a power-efficient alternative by detecting scene changes.

Purpose of the Study:

  • To propose a novel asynchronous circuit, the spiking elementary motion detector (sEMD), for processing event-based vision data.
  • To enable rapid distance estimation to close-by objects for collision avoidance in small, fast-moving agents.
  • To demonstrate the sEMD's application in robotic navigation and its potential for other sensory processing.

Main Methods:

  • Designed a novel asynchronous circuit (sEMD) using a single silicon neuron and synapse.
  • Encoded time-to-travel into spike bursts, with burst frequency proportional to event speed.
  • Utilized adaptive nonlinear synaptic efficacy scaling for refining time-to-travel estimates from inter-spike intervals.

Main Results:

  • The sEMD successfully detected elementary motion from event-based vision data.
  • A fast, albeit imprecise, time-to-travel estimate was obtained from initial spikes, refined by subsequent intervals.
  • The sEMD computed a collision avoidance direction for robotic navigation in a cluttered outdoor environment, comparable to frame-based algorithms.

Conclusions:

  • The sEMD provides an efficient method for collision avoidance using event-based vision sensors.
  • The underlying computational principle is a generic spiking temporal correlation detector applicable to diverse sensory modalities.
  • This work offers a novel perspective on information gating within spiking neural networks.