Abstract:Aiming at cooperative robot, a flexible array type tactile sensor is independently developed and packaged into a tactile handle that can sense the grip posture and force of human hand. A convolutional neural network (CNN)based method is proposed, which can distinguish the three modes of loose griping, tight griping and inadvertently touching the tactile handle. The recognition accuracy reaches 982%. A variable admittance control strategy is proposed to adjust the virtual damping of the manipulator in real time according to the state with which human hand grasps the handle. Based on this tactile handle, the local posture change of human hand can be sensed in real time, the operator operation intention can be accurately estimated, and the local perception information is transmitted to the robot to control its motion. Taking the UR collaborative robot as the experiment platform, using the tactile handle as the perceptual input, the humancomputer interaction experiment was conducted, and the motion accuracy of the manipulator was evaluated. Experiment results show that the tactile handle has good intentional perception capability.