Video-based slip sensor for multidimensional information detecting in deformable object grasp

Abstract

Efficient and reliable slip sensor plays a critical role in grasp of deformable object. This paper provides a new method for slip detection based on video processing, which can offer multidimensional sensing information and it is applicable for gripping deformable objects. The macro camera mounted inside the gripper can capture the dynamic slip and distortion of the object. The features of interest points, detected by the SURF algorithm in subsequent frames, are used to identify the properties of object and calculate the object’s changes. To determine the object’s slippage, nine detecting windows in the camera view can detect nine tracks of the slippage. Besides, the object’s distortion and direction of tangential force on the surface can be determined from these tracks, which helps to the estimation of the object’s damage. Experiments on homogeneous and textured materials show that this method can detect the object’ slippage accurately, and meanwhile provides the tracks of the slippage, distortion information and the force situation. Furthermore, tests for comparison were carried out and the results show that this sensor has a high accuracy in detecting slippage and distortion and the error is acceptable, which has an significant impact in deformable object grasp.