RECAST: Recasting Vision-Language Semantics into an Actionable Cost Map for Robot Navigation
cs.RO, cs.AI
Submitted: 2026-09-26
Updated: 2026-09-26
Project page: https://recast-nav.github.io
Terminology
Sources
- NavDP: Learning Sim-to-Real Navigation Diffusion Policy with Privileged Information Guidance
- From Seeing to Experiencing: Scaling Navigation Foundation Models with Reinforcement Learning
- Ground Slow, Move Fast: A Dual-System Foundation Model for Generalizable Vision-and-Language Navigation
- Embodied Navigation Foundation Model
- Do What You Say: Steering Vision-Language-Action Models via Runtime Reasoning-Action Alignment Verification
- DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Driving
- \textsc{NaVIDA}: Vision-Language Navigation with Inverse Dynamics Augmentation
- GPT-Driver: Learning to Drive with GPT
- Slow Brain, Fast Planner: Latency-Resilient VLM-Augmented Urban Navigation
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- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
- Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving