Ring attractor bio-inspired neural network for social robot navigation

Rivero-Ortega, Jesús D., Mosquera-Maturana, Juan S., Pardo-Cabrera, Josh, Hurtado-López, Julián, Hernández, Juan D. ORCID: https://orcid.org/0000-0002-9593-6789, Romero-Cano, Victor ORCID: https://orcid.org/0000-0003-2910-5116 and Ramírez-Moreno, David F. 2023. Ring attractor bio-inspired neural network for social robot navigation. Frontiers in Neurorobotics 17 , 1211570. 10.3389/fnbot.2023.1211570

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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 Random Tree Star methods using the Social Individual Index and Relative Motion Index as metrics in simulated experiments. We created a virtual scenario of a pedestrian area with various obstacles and dynamic agents. Results: The results obtained in our experiments demonstrate the effectiveness of this architecture in guiding a social agent while avoiding obstacles, and the metrics used for evaluating the system indicate that our proposal outperforms the widely used Social Force Model. Discussion: Our approach points to improving safety and comfort specifically for human-robot interactions. By integrating the Social Individual Index and Relative Motion Index, this approach considers both social comfort and collision avoidance features, resulting in better human-robot interactions in a crowded environment.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Computer Science & Informatics
Additional Information:	A correction to this article has been published: Rivero-Ortega JD, Mosquera-Maturana JS, Pardo-Cabrera J, Hurtado-López J, Hernández JD, Romero-Cano V and Ramírez-Moreno DF (2023) Corrigendum: Ring attractor bio-inspired neural network for social robot navigation. Front. Neurorobot. 17:1304597. doi: 10.3389/fnbot.2023.1304597
Publisher:	Frontiers Media
ISSN:	1662-5218
Related URLs:	https://doi.org/10.3389/fnbot.2023.13045...
Date of First Compliant Deposit:	21 October 2023
Date of Acceptance:	14 August 2023
Last Modified:	08 Jul 2024 09:23
URI:	https://orca.cardiff.ac.uk/id/eprint/163351

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