From reactive to cognitive: brain-inspired spatial intelligence for embodied agents

• URL: http://arxiv.org/abs/2508.17198v1
• Date: Sun, 24 Aug 2025 03:20:48 GMT
• Title: From reactive to cognitive: brain-inspired spatial intelligence for embodied agents
• Authors: Shouwei Ruan, Liyuan Wang, Caixin Kang, Qihui Zhu, Songming Liu, Xingxing Wei, Hang Su,
• Abstract summary: Brain-inspired Spatial Cognition for Navigation (BSC-Nav) is a unified framework for constructing and leveraging structured spatial memory in embodied agents.<n> BSC-Nav builds allocentric cognitive maps from egocentric trajectories and contextual cues, and dynamically retrieves spatial knowledge aligned with semantic goals.
• Score: 50.99942960312313
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Spatial cognition enables adaptive goal-directed behavior by constructing internal models of space. Robust biological systems consolidate spatial knowledge into three interconnected forms: \textit{landmarks} for salient cues, \textit{route knowledge} for movement trajectories, and \textit{survey knowledge} for map-like representations. While recent advances in multi-modal large language models (MLLMs) have enabled visual-language reasoning in embodied agents, these efforts lack structured spatial memory and instead operate reactively, limiting their generalization and adaptability in complex real-world environments. Here we present Brain-inspired Spatial Cognition for Navigation (BSC-Nav), a unified framework for constructing and leveraging structured spatial memory in embodied agents. BSC-Nav builds allocentric cognitive maps from egocentric trajectories and contextual cues, and dynamically retrieves spatial knowledge aligned with semantic goals. Integrated with powerful MLLMs, BSC-Nav achieves state-of-the-art efficacy and efficiency across diverse navigation tasks, demonstrates strong zero-shot generalization, and supports versatile embodied behaviors in the real physical world, offering a scalable and biologically grounded path toward general-purpose spatial intelligence.

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