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Robot teaching playback based on machine vision and human hand demonstration

The manufacturing industry has gradually developed from mass production to personalized customization, which requires a highly flexible robotic automated production line in manufacturing to deal with rapid retrofits of products. Industrial robots need to be taught the steps of completing tasks when dealing with new tasks. At present, the traditional robot teaching reproduction has many disadvantages, such as the complicated teaching system, the high cost, the waste of time, and the special training that operators need. In view of the above situation, a kind of teaching-playback based on machine vision and human hand demonstration was proposed in this paper. The position and orientation of the human fingertip during the execution of the mission were obtained by the Kinect sensor, and the pose information was transformed into the robot base coordinate system by coordinate transformation. The coordinate information was then transmit to the robot to enable the robot to quickly grab and place the target object. The feasibility and effectiveness of the teaching-playback system were proved by the experiment of picking and placing cylindrical workpiece.