Pondering the Way: Spatial-perceiving World Action Model for Embodied Navigation
Existing world model-based planners for visual navigation typically follow a verification-centric paradigm, decoupling goal intent from trajectory synthesis. This approach suffers from candidate dependence, heavy computational overhead, and inconsistencies between sampled actions and predicted visuals. To address these issues, we propose SWAM (Spatial-perceiving World Action Model), a task-centric joint observation-action generation framework. Given start and goal RGB observations, SWAM performs single-pass inference to simultaneously generate intermediate RGB-D sequences and corresponding action trajectories, promoting goal-consistent trajectory generation and improved spatial feasibilit...
| Authors | Hong Chen, Daqi Liu, Zehan Zhang et al. |
|---|---|
| Primary category | cs.RO |
| Published | 29 June 2026 |
| Last updated at source | 29 June 2026 |
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