Towards Unified World Models for Visual Navigation via Memory-Augmented Planning and Foresight

Understand

Enabling embodied agents to imagine future states is essential for robust and generalizable visual navigation.

• Yet, state-of-the-art systems typically rely on modular designs that decouple navigation planning from visual world modeling, which often induces state-action misalignment and weak adaptability in novel or dynamic scenarios.
• We propose UniWM, a unified, memory-augmented world model that integrates egocentric visual foresight and planning within a single multimodal autoregressive backbone.
• UniWM explicitly grounds action selection in visually imagined outcomes, tightly aligning prediction with control.