Going Places: Place Recognition in Artificial and Natural Systems

TL;DR

The paper addresses the problem of place recognition across biological and artificial agents by surveying computational methods, neural mechanisms, and human spatial cognition. It synthesizes cross-domain principles and proposes a unifying framework highlighting convergent strategies such as multimodal cue integration, memory management, and topological representations. Artificial systems emphasize scalable, data-driven architectures for robust localization, while biology contributes embodied, multimodal navigation strategies and semantic layers from human cognition. The work provides practical guidance for designing robust, generalizable place-recognition systems and identifies key challenges—generalization, robustness, and environmental variability—that span robots, animals, and humans.

Abstract

Place recognition, the ability to identify previously visited locations, is critical for both biological navigation and autonomous systems. This review synthesizes findings from robotic systems, animal studies, and human research to explore how different systems encode and recall place. We examine the computational and representational strategies employed across artificial systems, animals, and humans, highlighting convergent solutions such as topological mapping, cue integration, and memory management. Animal systems reveal evolved mechanisms for multimodal navigation and environmental adaptation, while human studies provide unique insights into semantic place concepts, cultural influences, and introspective capabilities. Artificial systems showcase scalable architectures and data-driven models. We propose a unifying set of concepts by which to consider and develop place recognition mechanisms and identify key challenges such as generalization, robustness, and environmental variability. This review aims to foster innovations in artificial localization by connecting future developments in artificial place recognition systems to insights from both animal navigation research and human spatial cognition studies.