Modeling, Simulation, and Application of Spatio-Temporal Characteristics Detection in Incipient Slip

TL;DR

This paper introduces a novel spatio-temporal modeling approach for incipient slip detection in robotic grasping, enhancing adaptability and accuracy across diverse conditions using strain-based sensing and simulations.

Contribution

It presents a new method linking strain rate extremes to slip states, enabling comprehensive detection of slip dynamics and application to vision-based tactile sensors.

Findings

Effective slip detection across various contact conditions

Accurate friction parameter estimation

Improved adaptive grasping control

Abstract

Incipient slip detection provides critical feedback for robotic grasping and manipulation tasks. However, maintaining its adaptability under diverse object properties and complex working conditions remains challenging. This article highlights the importance of completely representing spatio-temporal features of slip, and proposes a novel approach for incipient slip modeling and detection. Based on the analysis of localized displacement phenomenon, we establish the relationship between the characteristic strain rate extreme events and the local slip state. This approach enables the detection of both the spatial distribution and temporal dynamics of stick-slip regions. Also, the proposed method can be applied to strain distribution sensing devices, such as vision-based tactile sensors. Simulations and prototype experiments validated the effectiveness of this approach under varying contact conditions, including different contact geometries, friction coefficients, and combined loads. Experiments demonstrated that this method not only accurately and reliably delineates incipient slip, but also facilitates friction parameter estimation and adaptive grasping control.