Incipient Slip-Based Rotation Measurement via Visuotactile Sensing During In-Hand Object Pivoting

TL;DR

This paper introduces a visuotactile sensing method for real-time rotation measurement during in-hand object pivoting, accounting for incipient slip to improve accuracy and stability in robotic manipulation.

Contribution

It presents a generalized 2D contact model and a slip-aware rotation estimation method using line features, without requiring training data.

Findings

Achieved average static error of 0.17 degrees

Achieved average dynamic error of 1.34 degrees

Method operates in real-time during pivoting

Abstract

In typical in-hand manipulation tasks represented by object pivoting, the real-time perception of rotational slippage has been proven beneficial for improving the dexterity and stability of robotic hands. An effective strategy is to obtain the contact properties for measuring rotation angle through visuotactile sensing. However, existing methods for rotation estimation did not consider the impact of the incipient slip during the pivoting process, which introduces measurement errors and makes it hard to determine the boundary between stable contact and macro slip. This paper describes a generalized 2-d contact model under pivoting, and proposes a rotation measurement method based on the line-features in the stick region. The proposed method was applied to the Tac3D vision-based tactile sensors using continuous marker patterns. Experiments show that the rotation measurement system could achieve an average static measurement error of 0.17 degree and an average dynamic measurement error of 1.34 degree. Besides, the proposed method requires no training data and can achieve real-time sensing during the in-hand object pivoting.