ODG-NoMaD: Overhead-Camera Direction-Guided NoMaD
NoMaD [31] is a learned vision-navigation policy that unifies goal-conditioned navigation and exploration in a single goal-masked diffusion policy. In an unseen environment, however - where neither a goal image nor a topological map is available - it can only explore undirectedly, wandering without global awareness. We present ODG-NoMaD, which gives NoMaD's exploration mode a global sense of where to proceed, without retraining the policy. An overhead depth camera is used once on deployment to build an occupancy map and plan a global path, which is segmented to yield a desired heading; a per-frame traversability map from the robot's onboard depth then refines this into a collision-free di...
| Authors | Blossom Treesa Bastian, Keerthi S. Shetty, Manish Kolachalam et al. |
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| Primary category | cs.RO |
| Published | 3 August 2026 |
| Last updated at source | 3 August 2026 |
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