D-CLING: Prior-Preserving Depth-Conditioned Fine-Tuning for Navigation Foundation Models

Navigation Foundation Models (NFMs) trained on large cross-embodied datasets have demonstrated powerful generalizability in various scenarios. Adopting in-domain fine-tuning for an NFM efficiently calibrates the visuomotor policy, promising further improvement even in a novel scenario. However, the ...