发表机构
Shenzhen University; Great Bay University; China Pharmaceutical University; The University of Hong Kong; Tsinghua University; École Polytechnique Fédérale de Lausanne (EPFL); University of Belgrade（深圳大学; 大湾区大学; 中国药科大学; 香港大学; 清华大学; 洛桑联邦理工学院; 贝尔格莱德大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对机器人盲文阅读中接触建立不足的问题，提出自适应接触框架，通过多头策略学习模仿专家调整接触，在20块盲文板上实现94.0%触觉质量和88.6%重建，验证主动接触对可靠识别的重要性。
AI 中文摘要
对于盲人而言，触觉是通过盲文获取书面信息的重要渠道。要让机器人具备类似的能力，不仅需要识别触觉模式，还需要主动建立使这些模式可读的物理接触。然而，现有的机器人盲文阅读器大多侧重于接触后的识别，而接触建立本身尚未得到充分解决。我们提出了一种用于机器人触觉盲文阅读的自适应接触框架，该框架在识别和重建之前评估接触质量并物理纠正不合适的接触。多头策略学习利用专家引导的接触调整演示，联合学习接触可接受性和姿态修正。在部署期间，机器人迭代评估并重新建立接触，保留可靠的触觉观测用于姿态感知融合和盲文重建。在用于学习和评估的20块物理盲文板上，所提出的方法在十块在线评估板上实现了94.0%的触觉质量和88.6%的触觉重建。这些结果表明，主动建立可读接触的重要性，而不是仅仅依赖于在不完美的触觉观测下的识别，以实现可靠的机器人盲文阅读。
英文摘要
For people who are blind, touch provides an essen-tial channel for accessing written information through Braille. Bringing a similar capability to robots requires them not only to recognize tactile patterns, but also to actively establish physical contact that makes those patterns readable. Yet existing robotic Braille readers largely focus on recognition after contact, leaving contact establishment itself insufficiently addressed. We present an adaptive-contact framework for robotic tactile Braille reading that assesses contact quality and physically corrects unsuitable contact before recognition and reconstruc-tion. Multi-Head Policy Learning uses expert-guided contact-adjustment demonstrations to jointly learn contact acceptability and pose corrections. During deployment, the robot iteratively evaluates and re-establishes contact, retaining reliable tactile observations for pose-aware fusion and Braille reconstruction. Across 20 physical Braille plates used for learning and eval-uation, the proposed approach achieves 94.0% tactile quality and 88.6% tactile reconstruction on the ten online-evaluation plates. These results demonstrate the importance of actively establishing readable contact, rather than relying solely on recognition under imperfect tactile observations, for reliable robotic Braille reading.
