Detecting and Controlling Slip through Estimation and Control of the Sliding Velocity

Abstract

Slipping detection and avoidance are key issues in dexterous robotic manipulation. The capability of robots to grasp and manipulate objects of common use can be greatly enhanced by endowing these robots with force/tactile sensors on their fingertips. Object slipping can be caused by both tangential and torsional loads when the grip force is too low. Contact force and moment measurements are required to counteract such loads and avoid slippage by controlling the grip force. In this paper, we use the SUNTouch force/tactile sensor, which provides the robotic control system with reliable measurements of both normal and tangential contact force components together with the torsional moment. By exploiting the limit surface concept and the LuGre friction model, we build a model of the object/fingertip planar sliding. This model is the basis of a nonlinear observer that estimates the sliding velocity and the friction state variable from the measured contact force and torsional moment. The slipping control system uses the estimated friction state to detect the slipping event and the estimated sliding velocity to control the grasp force. The control modality is twofold: the first one is aimed at avoiding object slip, while the second one allows the object to perform a controlled pivoting about the grasping axis. Experiments show that the robot is able to safely manipulate objects that require grasping forces in a large range, from 0.2 N to 10 N. This level of manipulation autonomy is attained by a suitably identified dynamic model that overcomes the limited generalization capability of existing learning-based approaches in the general roto-translational slip control.