Anti-Slipping Adaptive Grasping Control with a Novel Optoelectronic Soft Sensor

Grasping control is one of the key features of robot manipulation. Slipping detection, avoidance, and minimum force grasping are of primary concern since it is expected that robot manipulators have similar performance to human hands. In this work, a new type of optoelectronic sensor, which has a human-like soft skin but a simple design, is applied to slip motion control. Based on the model of this soft sensor and the robotic gripper, we describe a model reference adaptive controller (MRAC) to estimate unknown system parameters for grasping random objects. Update laws for unknown parameters are chosen by stability analysis and the system feasibility is illustrated through both numerical simulation and hardware experiment.