Ring attractor bio-inspired neural network for robot social navigation.

ABSTRACT:

Introduction

We introduce a bio-inspired navigation system for a robot to guide a social agent to a target location while avoiding static and dynamic obstacles. Robot navigation can be accomplished through a model of ring attractor neural networks. This connectivity pattern between neurons enables the generation of stable activity patterns that can represent continuous variables such as heading direction or position. The integration of sensory representation, decision-making, and motor control through ring attractor networks offers a biologically-inspired approach to navigation in complex environments.

Methods

The navigation system is divided into perception, planning, and control stages. Our approach is compared to the widely-used Social Force Model and Rapidly Exploring Ra

SUBMITTER: Rivero-Ortega JD 

PROVIDER: S-EPMC10501606 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature