Communication Dans Un Congrès Année : 2025

Visual Homing in Outdoor Robots Using Mushroom Body Circuits and Learning Walks

Résumé

Ants achieve robust visual homing with minimal sensory input and only a few learning walks, inspiring biomimetic solutions for autonomous navigation. While Mushroom Body (MB) models have been used in robotic route following, they have not yet been applied to visual homing. We present the first real-world implementation of a lateralized MB architecture for visual homing onboard a compact autonomous carlike robot. We test whether the sign of the angular path integration (PI) signal can categorize panoramic views, acquired during learning walks and encoded in the MB, into "goal on the left" and "goal on the right" memory banks, enabling robust homing in natural outdoor settings. We validate this approach through four incremental experiments: (1) simulation showing attractor-like nest dynamics; (2) real-world homing after decoupled learning walks, producing nest search behavior; (3) homing after random walks using noisy PI emulated with GPS-RTK; and (4) precise stopping-at-the-goal behavior enabled by a fifth MB Output Neuron (MBON) encoding goal-views to control velocity. This mimics the accurate homing behavior of ants and functionally resembles waypoint based position control in robotics, despite relying solely on visual input. Operating at 8 Hz on a Raspberry Pi 4 with 32×32 pixel views and a memory footprint under 9 kB, our system offers a biologically grounded, resource-efficient solution for autonomous visual homing.

Fichier principal
Vignette du fichier
pczhjzttxtbdcpzyddhffcrptdbpmsrk.pdf (1.93 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence

Dates et versions

hal-05160353 , version 1 (13-07-2025)

Licence

Identifiants

  • HAL Id : hal-05160353 , version 1

Citer

Gabriel G Gattaux, Julien R Serres, Franck Ruffier, Antoine Wystrach. Visual Homing in Outdoor Robots Using Mushroom Body Circuits and Learning Walks. The 14th International Conference on Biomimetics and Biohybrid Systems, Living Machines, University of Sheffield, Jul 2025, Sheffield, United Kingdom. ⟨hal-05160353⟩
729 Consultations
106 Téléchargements

Partager

  • More