Incipient Slip Detection by Vibration Injection into Soft Sensor

TL;DR

Incipient slip detection is addressed by estimating the stick ratio $s$ at the contact surface through a macroscopic soft-structure vibration mechanism. The method injects vibrations into a soft tactile sensor, so that $s$-dependent deformation modulates the frequency spectrum, allowing a single sensor to infer slip via a regression model $s_t = f(\phi(x_{t-T:t}))$. A data-driven SVR slip model is trained on data with Gaussian vibration and evaluated against vibrotactile and pressure-distribution baselines, achieving lower RMSE and improved stabilization performance. The approach reduces sensor complexity while remaining robust across materials, enabling practical grip stabilization without high-density sensor arrays or optical systems.

Abstract

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.

Figures (13)

• Figure 1: Incipient slip detection with vibration injection achieves stick-ratio stabilization. Propagated vibration reveals stick ratio and provides a degree of incipient slip and stabilization controller feedback on the information.
• Figure 2: Comparison of incipient slip detection methods: (a)(b) Each conventional method has its advantages and disadvantages. (c) Proposed method has a mechanism that incorporates the best of both.
• Figure 3: Mechanism of our method for incipient slip detection using vibration injection: Completely stick contact surface without tangential force $F_T$ changes into an incipient slip with $F_T$. Estimating stick ratio with propagated vibration enables us to detect incipient slip.
• Figure 4: Slip experimental setup: Linear actuator and spring make tangential force $F_T$ and motion capture system detects precise object position $y$. Objects have identical geometry but are made from different materials by 3D printers for various friction coefficients and softness.
• Figure 5: Contact surface observation based on optical tactile sensor mechanism