N_0-VTLA：带潜在触觉令牌的视觉-触觉-语言-动作模型
原标题：N_0-VTLA: Scaling Vision-Tactile-Language-Action Model with Latent Tactile Tokens
AI 摘要
N_0-VTLA 是一个视觉-触觉-语言-动作（VTLA）基础模型，通过触觉感知和反馈控制实现精细的接触丰富操作，并支持从部署数据中进行离线策略改进。该模型采用视觉-触觉预训练、分阶段触觉通路集成和优势条件离线强化学习（ALTER）的训练方案，在九个真实机器人任务中全部获胜，并在二十任务模拟套件中达到63.8%的平均成功率，显著优于最强基线。
正文节选
N_0-VTLA: Scaling Vision-Tactile-Language-Action Model with Latent Tactile Tokens Abstract We present N_0-VTLA, a vision-tactile-language-action (VTLA) foundation model capable of (1) fine-grained contact-rich manipulation with tactile perception and tactile-feedback control, and (2) offline policy improvement from stored deployment data. Building on current vision-based backbones, we propose a training recipe for tactile integration consisting of visuo-tactile pre-training, staged tactile-pathw