In robotic manipulation, preventing objects from slipping and establishing a secure grip on them is critical. Successful manipulation requires tactile sensors that detect the microscopic incipient slip phenomenon at the contact surface. Unfortunately, the tiny signals generated by incipient slip are quickly buried by environmental noise, and precise stress-distribution measurement requires an extensive optical system and integrated circuits. In this study, we focus on the macroscopic deformation of the entire fingertip's soft structure instead of directly observing the contact surface and its role as a vibration medium for sensing. The proposed method compresses the stick ratio's information into a one-dimensional pressure signal using the change in the propagation characteristics by vibration injection into the soft structure, which magnifies the microscopic incipient slip phenomena into the entire deformation. This mechanism allows a tactile sensor to use just a single vibration sensor. In the implemented system, a biomimetic tactile sensor is vibrated using a white signal from a PZT motor and utilizes frequency spectrum change of the propagated vibration as features. We investigated the proposed method's effectiveness on stick-ratio estimation and \red{stick-ratio stabilization} control during incipient slip. Our estimation error and the control performance results significantly outperformed the conventional methods.

翻译：在机器人操作中，防止物体滑落并建立稳固的抓取至关重要。成功操作需要触觉传感器检测接触表面的微观初始滑移现象。然而，初始滑移产生的微弱信号极易被环境噪声淹没，而精确的应力分布测量需要复杂的光学系统和集成电路。本研究聚焦于指尖软结构的整体宏观变形，而非直接观测接触表面，并利用其作为振动介质的感知特性。所提出的方法通过向软结构注入振动，利用传播特性变化将粘附比信息压缩为一维压力信号，从而将微观初始滑移现象放大为整体变形。该机制使触觉传感器仅需单个振动传感器即可实现。在实现的系统中，仿生触觉传感器通过PZT电机施加白噪声信号激励振动，并以传播振动的频谱变化作为特征。我们评估了该方法在粘附比估计及初始滑移过程中的\red{粘附比稳定}控制效果。实验结果表明，所提方法的估计误差和控制性能均显著优于传统方法。