An Adaptive Semi-Autonomous Impedance Controller for Teleoperated Object Grasping Based on Human Grip Safety Margin

Humans can effortlessly grasp various objects when the fingers are in direct physical interaction with the object. However, the same actions become complicated when grasping has to be performed via a teleoperated remote robot due to a lack of direct contact and reduced sensory information. Having a fully autonomous remote robot can eliminate the problem of lack of proper feedback to the human operator, nevertheless, it also prevents human control over the remote robot's grasping actions. In this paper, we propose a semi-autonomous controller for a teleoperated robot grasping where the human operator controls the grasping aperture while the robot controls the impedance of the gripper. When the operator grasps an object with the remote robot, the semi-autonomous controller maintains the grip force by adjusting stiffness. The developed stiffness adjustment approach derives from the concept of grip force safety margin, which is the central regulation principle humans use to maintain a light grasp yet prevent object slippage. To detect incipient slippage, we use a tactile sensor that captures the local deformations due to the contact and interprets them to determine the proximity to the object's slip. To validate the proposed method, we performed experiments on a teleoperation system composed of Force Dimension sigma.7 haptic interface and a KUKA LBR iiwa collaborative robot equipped with a custom-built gripper. The results show that the proposed controller is robust to external perturbations while it adapts to the operator's commands to prevent grasped object slippage.