Efficient Break-Away Friction Ratio and Slip Prediction Based on Haptic Surface Exploration

Abstract

The break-away friction ratio (BF-ratio), which is the ratio between friction force and the normal force at slip occurrence, is important for the prediction of incipient slip and the determination of optimal grasping forces. Conventionally, this ratio is assumed constant and approximated as the static friction coefficient. However, this ratio varies with acceleration rates and force rates applied to the grasped object and the object material, which lead to difficulties in determining optimal grasping forces that avoid slip. In this paper, we propose a novel approach based on the interactive forces to allow a robotic hand to predict object slip before its occurrence. The approach only requires the robotic hand to have a short haptic surface exploration over the object surface before manipulating it. Then, the frictional properties of the finger-object contact can be efficiently identified, and the BFratio can be real-time predicted to predict slip occurrence under dynamic grasping conditions. Using the predicted BF-ratio as a slip, threshold is demonstrated to be more accurate than using the static/Coulomb friction coefficient. The presented approach has been experimentally evaluated on different object surfaces, showing good performance in terms of prediction accuracy, robustness, and computational efficiency.Index Terms-Break-away ratio, haptic surface exploration, slip prediction.

Stable Grip Control on Soft Objects With Time-Varying Stiffness

“…One possible approach would be to use a prior assumption of a conservative critical force and learn an optimum value using break-away force prediction using our previous results [23] together with a suitable method to estimate the parameters of a friction model [32]. Our approach in [23] was based on the parameter identification of LuGre friction model [33] where the sliding contact between two surfaces is modeled as interactions of micro-elastic bristles. The approach requires the robotic hand to perform a short stroke haptic surface exploration to estimate the frictional properties of the finger-object contact.…”

“…The break-away friction force is predicted at the state which results in a rapid increase in the bristles' displacements. A combination of the physical model based slip prediction approach in [23] with the proposed probabilistic approach for slip avoidance involves integrating slip detection to the controller. It will help to counter the uncertainty that comes from the friction coefficient itself though it is less crucial in the case of maintaining the grip at a given point as discussed in this paper.…”

“…[22]. Including our recent work [23], methods to identify parameters of friction models by interacting with rigid objects have been studied elsewhere [24]. However, to the best of our knowledge, this is the first time a mathematical model is proposed to control the grip forces on a variable impedance object by estimating the probability of failure.…”

Global estimation of an object’s pose using tactile sensing

“…This approach has been previously validated by the authors in Liu et al [48] showing an accuracy of 0.224 mm in contact location, corresponding to an error of 1.5 • in contact normal. This sensing strategy has found several successful applications, ranging from slip detection [49] to surface following [50]. …”

A visuo-tactile control framework for manipulation and exploration of unknown objects

“…A key factor for these skills is the highly developed integration of the visual, tactile, and force sensing channels when carrying out an action: this integration plays a major role to compensate for the numerous uncertainties involved in the mechanical interaction with an object when its properties (such as pose, shape, mass and friction) are not or only approximately known [3], [20], [8]. While the restricted availability of good tactile sensors has been for a long time a major impediment for a broader development of similar capabilities for robots, the accelerating progress in tactile sensing and its availability for robot manipulators is now increasingly opening up exciting possibilities for integrating touch and vision to enhance dexterous manipulation skills of robots.…”