Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Wavelet-based visual compass.

PloS one·2026
Same author

Introduction to the Proceedings of the CNS*2025 Meeting.

Journal of computational neuroscience·2026
Same author

Efficient event-based delay learning in spiking neural networks.

Nature communications·2025
Same author

Building on models-a perspective for computational neuroscience.

Cerebral cortex (New York, N.Y. : 1991)·2025
Same author

Understanding the mechanism of facilitation in hoverfly TSDNs.

PLoS computational biology·2025
Same author

Ant visual route navigation: How the fine details of behaviour promote successful route performance and convergence.

PLoS computational biology·2025
Same journal

If Turing Played Piano With an Artificial Partner.

Artificial life·2026
Same journal

Discovering Partial Differential Equations With Neural Cellular Automata.

Artificial life·2026
Same journal

Book Review: Exploring the Boundaries of Life-as-It-Is.

Artificial life·2026
Same journal

System 0/1/2/3: Quad-Process Theory for Multitimescale Embodied Collective Cognitive Systems.

Artificial life·2025
Same journal

To Engineer an Angel, First Validate the Devil: Analyzing the "Could Be" in Artificial Life's "Life as-It-Could-Be".

Artificial life·2025
Same journal

Untapped Potential in Self-Optimization of Hopfield Networks: The Creativity of Unsupervised Learning.

Artificial life·2025
See all related articles

Related Experiment Video

Updated: Jun 8, 2025

Practical Methodology of Cognitive Tasks Within a Navigational Assessment
05:19

Practical Methodology of Cognitive Tasks Within a Navigational Assessment

Published on: June 1, 2015

13.6K

Investigating the Limits of Familiarity-Based Navigation.

Amany Azevedo Amin1, Efstathios Kagioulis2, Norbert Domcsek2

  • 1University of Sussex, Department of Informatics. aa2645@sussex.ac.uk.

Artificial Life
|November 1, 2024
PubMed
Summary
This summary is machine-generated.

Robotic navigation using insect-inspired familiarity-based strategies can navigate longer routes with smaller neural networks. Performance depends on view acquisition rate and input dimension, with potential for computational savings in power-constrained robots.

Keywords:
Navigationinsect-inspiredneural networksrapid learningrobotics

More Related Videos

Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation
20:12

Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation

Published on: October 8, 2011

30.5K
Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function
06:17

Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

Published on: January 26, 2024

1.9K

Related Experiment Videos

Last Updated: Jun 8, 2025

Practical Methodology of Cognitive Tasks Within a Navigational Assessment
05:19

Practical Methodology of Cognitive Tasks Within a Navigational Assessment

Published on: June 1, 2015

13.6K
Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation
20:12

Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation

Published on: October 8, 2011

30.5K
Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function
06:17

Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

Published on: January 26, 2024

1.9K

Area of Science:

  • Robotics
  • Computational Neuroscience
  • Artificial Intelligence

Background:

  • Insect-inspired navigation offers solutions for power-constrained robots.
  • Familiarity-based navigation uses a single-layer neural network and Infomax learning rule.
  • Previous work demonstrated navigation up to 60m.

Purpose of the Study:

  • Investigate the limits of familiarity-based navigation for longer routes.
  • Determine optimal parameters for effective robot navigation.
  • Inform insect navigation theories and improve robotic deployments.

Main Methods:

  • Challenged the method to navigate longer routes.
  • Investigated performance, view acquisition rate and dimension, network size, and robustness to noise.
  • Analyzed network weights and reliance on specific image areas.

Main Results:

  • Effective memorization of familiar views is possible for longer routes, but decreases with reduced input view dimensions.
  • Increased view acquisition rate is necessary for consistent performance with longer routes.
  • Network size can be reduced with equivalent performance, offering computational and memory savings.

Conclusions:

  • Familiarity-based navigation is scalable to longer routes with adjusted parameters.
  • Optimal performance requires balancing view acquisition rate, input dimension, and network size.
  • The method shows robustness to noise and provides insights into insect navigation mechanisms.