仿真中预训练视觉灵巧操作
Original title: Pre-training Visual Dexterity in Simulation
IndustryAI 78
Source: arXiv cs.ROPublish time unverified
arXiv:2608.15917v2 Announce Type: replace Abstract: Large-scale pre-training has made robot policy fine-tuning increasingly data-efficient, but this progress has largely been driven by datasets and embodiments built around simple parallel-jaw grippers. Dexterous, multi-fingered hands remain comparatively data-starved because real teleoperation is costly to scale, while human hand video is off-embodiment and requires lossy pose estimation and retargeting.