CoFL: Continuous Flow Fields for Language-Conditioned Navigation
Existing language-conditioned navigation systems typically rely on modular pipelines or trajectory generators, but the latter use each scene--instruction annotation mainly to supervise one start-conditioned rollout. To address these limitations, we present CoFL, an end-to-end policy that maps a bird's-eye view (BEV) observation and a language instruction to a continuous flow field for navigation. CoFL reformulates navigation as workspace-conditioned field learning rather than start-conditioned trajectory prediction: it learns local motion vectors at arbitrary BEV locations, turning each scene--instruction annotation into dense spatial control supervision. Trajectories are generated from a...
| Authors | Haokun Liu, Zhaoqi Ma, Yicheng Chen et al. |
|---|---|
| Primary category | cs.RO |
| Published | 3 March 2026 |
| Last updated at source | 29 April 2026 |
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