Signal processing of direct teaching data for human-robot cooperation

Generally, industrial robot has been used in the automate producing process and the repetitive process on behalf of human. Recently, the interest in the human-robot cooperative industrial robot which can work together with human through physical interaction in the same space has been increased. Human-robot cooperation technology can allow to combine work intelligence of human with high performance of the robot. Also, the direct teaching technology enables an operator who is not used to robot programming to control the robot easily by teaching the task trajectory directly. To improve the robot performance in the direct teaching technology, it is important to separate the precise teaching signal from the external FT sensor signal because the operator inputs the command by grabbing the end-effector of the robot with FT sensor. We has analyzed FT sensor data to apply to teaching control algorithm and compared various filtering methods to obtain smooth control capability.