LingBot-Touch：面向通用灵巧操作的异构触觉表征学习
原标题：Paper page - Learning Heterogeneous Tactile Representation for General Dexterous Manipulation
AI 摘要
研究团队提出触觉基础模型 LingBot-Touch，学习跨压阻、磁性和视触觉等异构触觉传感器的统一可扩展表征，生成即插即用的触觉 token。这些 token 可无缝集成到扩散策略及 π_{0.5}、LingBot-VLA 等视觉-语言-动作模型中，持续提升操作灵巧性。仿真与多硬件平台真机实验表明，该表征在保持计算效率的同时显著有益于复杂操作任务，为利用跨传感器数据扩展触觉学习提供思路。
正文节选
Learning Heterogeneous Tactile Representation for General Dexterous Manipulation Abstract LingBot-Touch is a tactile foundation model that learns a unified, extensible representation across heterogeneous tactile sensors, yielding plug-and-play tactile tokens that consistently enhance manipulation policies such as diffusion policy and VLA models. Tactile sensing is an indispensable modality for contact-rich dexterous manipulation, a capability that hints at the ultimate frontiers of embodied inte