Mutual Guidance Diffusion for Object Navigation

Modular object-goal navigation (ObjectNav) typically constructs a semantic map and then plans from that map as a fixed condition. Under partial observability, however, route selection and beliefs about unobserved space are coupled: a route determines which future regions matter, while plausible future layouts constrain which routes are executable. We introduce MGNav, a dual-branch diffusion framework that jointly generates future waypoints and waypoint-aligned semantic layouts. At every denoising step, gated bidirectional cross-attention lets evolving route hypotheses constrain layout imagination and lets imagined free space, obstacles, and semantic context refine the route. This interaction targets a mismatch between separately optimized perception and planning modules rather than merely adding an auxiliary prediction task. Experiments on Gibson and Matterport3D show consistent gains over a trajectory-diffusion baseline and over controlled concatenation and ungated cross-attention alternatives. We also state the additional trajectory and layout supervision required by our method and analyze the assumptions and failure modes of coupled generation.