GRAFT：细粒度机器人操作的高效在线强化适配
Original title: GRAFT: Grounded and Efficient Online Reinforcement Adaptation for Fine-Grained Robot Manipulation
ResearchAI 75
Source: arXiv cs.ROPublish time unverified
arXiv:2608.27079v2 Announce Type: replace Abstract: Pretrained vision-language-action (VLA) policies provide strong priors for robot manipulation, yet adapting them online to fine-grained biomedical tasks remains challenging. Task success often hinges on subtle, view-dependent visual cues, while task-level rewards provide little guidance about which regions matter, making it difficult to learn task-relevant visual grounding from limited real-robot interaction.