COLSON applies diffusion models to reinforcement learning for social robot navigation and adds controllability mechanisms that enable zero-shot adaptation to unseen static obstacles and altered objectives.
Mobile Robot Navigation Using Learning-Based Method Based on Predictive State Representation in a Dynamic Environment
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COLSON: Controllable Learning-Based Social Navigation via Diffusion-Based Reinforcement Learning
COLSON applies diffusion models to reinforcement learning for social robot navigation and adds controllability mechanisms that enable zero-shot adaptation to unseen static obstacles and altered objectives.