Compliant Grasping Control for a Tactile Self-Sensing Soft Gripper.

Abstract

Soft grippers with good passive compliance can effectively adapt to the shape of a target object and have better safe grasping performance than rigid grippers. However, for soft or fragile objects, passive compliance is insufficient to prevent grippers from crushing the target. Thus, to complete nondestructive grasping tasks, precision force sensing and control are immensely important for soft grippers. In this article, we proposed an online learning self-tuning nonlinearity impedance controller for a tactile self-sensing two-finger soft gripper so that its grasping force can be controlled accurately. For the soft gripper, its grasping force is sensed by a liquid lens-based optical tactile sensing unit that contains a self-sensing fingertip and a liquid lens module and has many advantages of a rapid response time (about 0.04 s), stable output, good sensitivity (>0.4985 V/N), resolution (0.03 N), linearity (R² > 0.96), and low cost (power consumption: 5 mW, preparation cost