让机器人通过可操控的VLA模型自主习得新技能，突破演示数据限制
arXiv:2606.24884v1 Announce Type: cross Abstract: Vision-language-action (VLA) models can learn manipulation skills from demonstrations, but their cap…
对比学习新范式：用动作和图像联合预训练，显著提升机器人视觉运动控制性能。
arXiv:2606.17256v1 Announce Type: cross Abstract: Existing vision encoders for robotics face a fundamental bottleneck: robotic datasets lack the scale…
多智能体上下文学习让双手机器人协作更灵活，看论文如何突破复杂操控难题
arXiv:2604.20348v2 Announce Type: replace-cross Abstract: Language Models (LLMs) have emerged as powerful reasoning engines for embodied control. In p…
新提出的通用双数字接口YUBI，实现大规模双手灵巧操作，开启机器人精细操控新篇章。
arXiv:2606.10244v1 Announce Type: cross Abstract: We introduce Yielding Universal Bidigital Interface (YUBI), a finger-aligned gripper designed to ena…
提出短视意图模型IntentVLA，解决机器人模仿数据多模态歧义问题，提升操作准确性
arXiv:2605.14712v1 Announce Type: cross Abstract: Robot imitation data are often multimodal: similar visual-language observations may be followed by d…