Autonomous Grasping of a Space Robot Multisensory Gripper

Most robot grippers can hardly be applied to space service due to their devoid of the ability of outputting large force, autonomously making decision and sensing the environment. In this paper, a space underactuated gripper which can stably grasp various objects based on fewer actuators, large force and autonomous decision and multisensory information feedback is introduced. Firstly, the versatile grasping patterns of the gripper with characteristics of underactuation are presented. The multiple sensors are mounted on the gripper including PVDF contact force sensors, a line structure light sensor which detects grasped object approximate shape and volume, and a wrist force sensor which detects the grasped object mass. Secondly, autonomous grasping which is characterized by autonomous decision-making and control is focused on. Control strategies are also proposed to make proper prosthetics and stable grasping according to force sensors information. The grasping rules are extracted from original experiment sample data. Through fuzzy neural network, grasping map is established among comprehensive fuzzy features, including grasping task and object features, and the grasping patterns. Finally, the experimental results demonstrate that the gripper can achieve autonomous and stable grasping