SAGE: A Socially-Aware Generative Engine for Heterogeneous Multi-Agent Navigation
Researchers introduce SAGE, a generative engine designed for socially-aware navigation among heterogeneous multi-agent teams. SAGE uses a Heterogeneous Graph Transformer to model asymmetric interactions and a diffusion-based generative module for joint trajectory prediction and planning. A training-free safety-social energy guidance mechanism refines robot trajectories to enhance safety and social compliance. Experiments on real-world and synthetic datasets show that SAGE reduces collision and social-violation rates and scales to teams of up to 20 robots.
Why it matters: This work presents a scalable approach to safe and socially compliant robot navigation in complex, multi-agent environments, addressing key challenges in real-world deployment.
Full story at: arXiv Multiagent Systems ↗