Skill acquisition from human experts through pattern processing of teaching data

An approach to the teaching of manipulative skills is developed and applied to a deburring robot. Teaching data acquired from a human expert, who can perform an efficient job, are processed on a computer to attain his skilful manipulation strategies. The strategies are described by a group of control laws that relate sensor signals to motion commands. Sensor signals are processed by using pattern recognition techniques to interpret sensor information and to allow the robot to recognize the state of the process. The control laws designate which control action the robot should take in response to each signal pattern generated in the process. A method for driving a compact set of discrimination functions for real-time recognition of signal patterns is also discussed. The method is implemented on a direct-drive deburring robot. It is demonstrated that the robot can mimic the skilful manipulation of the human expert and perform the task efficiently