发表机构
Sun Yat-Sen University; Helmholtz-Zentrum Dresden-Rossendorf e.V.（中山大学; 德累斯顿亥姆霍兹研究中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出一种集成霍尔效应传感器与软磁复合材料的单元件触觉传感器，通过形变解耦压力和粘附信号，实现高精度双模态感知，提升机器人操作能力。
AI 中文摘要
将粘附性感知集成到仿人机器人的人工皮肤中，显著增强了其认知和操作能力。然而，现有的触觉传感器在多模态信号解耦和稳定性方面面临挑战。本文提出了一种表面柔软的触觉传感器，该传感器在坚固的弹性框架内集成了霍尔效应传感器和软磁复合材料。传感器表面在压力作用下凹陷，当从粘性表面撤回时明显凸起，动态改变霍尔传感器与磁体之间的距离。这产生了全过程可追踪且基线分离的信号，能够实时区分压力和拉脱力。这种单传感元件设计使得在同一接触点实现双模态感知，同时消除应力串扰，提高了准确性和灵敏度。坚固框架与磁-机械传感机制的融合，使传感器具有卓越的可靠性和优异的信号基线稳定性。该触觉传感器在评估粘附性能、监测橡胶老化、精确处理轻质物体以及认知自然物体表面特征方面，具有推动机器人能力发展的巨大潜力。
英文摘要
Integrating tackiness sensation into the artificial skin of humanoid robots significantly enhances their cognitive and operational capabilities. However existing tactile sensors face challenges in decoupling of the multimodal signal and stability. Here we present a surface-soft tactile sensor that incorporates a Hall effect sensor and a soft magnetic composite within a robust elastic framework. The sensor surface indents under pressure and bulges prominently when retracted from sticky surfaces dynamically altering the Hall sensor-magnet distance. This generates whole-process-traceable and baseline-separated signals enabling real-time differentiation between pressure and pull-off force. This single-sensing-element design facilitates bimodal sensing at the same contact spot while eliminate stress cross-talk enhancing both accuracy and sensitivity. The fusion of a robust framework and magneto-mechanical sensing mechanism equips the sensor with exceptional reliability and excellent signal baseline stability. This tactile sensor holds substantial potential for advancing robotic capabilities in evaluating adhesive properties monitoring rubber aging precisely handling lightweight objects and cognizing natural objects surface characteristics.
