Research on Operation Intention Based on Flexible Tactile Sensing Handle

In order to obtain and analyze the operator’s intention comprehensively and accurately in human-robot interaction, an array-type flexible tactile sensor was designed. The sensor was encapsulated into a tactile handle to sense the grasping state of the human hand in real time. According to the analysis of different operators’ grasping posture and grasping habits, the grasping state was defined as 5 modes. Based on Harris feature point positioning and extraction, a method of grasping posture conversion was proposed to ensure the completeness and standard of the extracted grasping features. A set of Convolutional Neural Networks (CNN) suitable for the real-time classification of the grasping intention was built to distinguish the grasping state sensed by the handle in real time, accurately determine the operator’s intention, and complete the interaction with the robot. Using a UR collaborative robot as the experimental platform and the haptic handle as the intent sensing device, the intent-behaviour mapping relationship was constructed to control the motion of the UR collaborative robot. The experimental results show that the classification accuracy of operation intention is as high as 97.87%.