Gridbot: An autonomous robot controlled by a spiking neural network mimicking the brain's navigational system

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

It is true that the "best" neural network is not necessarily the one with the most "brain-like" behavior. Understanding biological intelligence, however, is a fundamental goal for several distinct disciplines. Translating our understanding of intelligence to machines is a fundamental problem in robotics. Propelled by new advancements in Neuroscience, we developed a spiking neural network (SNN) that draws from mounting experimental evidence that a number of individual neurons is associated with spatial navigation. By following the brain's structure, our model assumes no initial all-to-all connectivity, which could inhibit its translation to a neuromorphic hardware, and learns an uncharted territory by mapping its identified components into a limited number of neural representations, through spike-timing dependent plasticity (STDP). In our ongoing effort to employ a bioinspired SNN-controlled robot to real-world spatial mapping applications, we demonstrate here how an SNN may robustly control an autonomous robot in mapping and exploring an unknown environment, while compensating for its own intrinsic hardware imperfections, such as partial or total loss of visual input.

Original languageEnglish (US)
Title of host publicationICONS 2018 - Proceedings of International Conference on Neuromorphic Systems 2018
PublisherAssociation for Computing Machinery
ISBN (Print)9781450365444
DOIs
StatePublished - Jul 23 2018
Event2018 International Conference on Neuromorphic Systems, ICONS 2018 - Knoxville, United States
Duration: Jul 23 2018Jul 26 2018

Publication series

NameACM International Conference Proceeding Series

Other

Other2018 International Conference on Neuromorphic Systems, ICONS 2018
Country/TerritoryUnited States
CityKnoxville
Period7/23/187/26/18

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

Keywords

  • Autonomicity
  • Neuromorphic robotics
  • Spatial navigation
  • Spiking neural networks

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