| Summary: | 碩士 === 國立臺灣大學 === 機械工程學研究所 === 107 === Owing to the applications of robot arm become increasingly extensive, dynamic pick-and-place on the production line has gradually increased. Through robot vision system and artificial intelligence , the requirements of operation personnel can be greatly reduced. The purpose of this thesis is the robot arm plugging control application. Combining robotics and artificial intelligence into robot systems, two tasks are achieved: random pick and place, and simulation of human wrist adjustment skew screws.
In this paper, we first implement the rotation, scale, translation-invariant template matching algorithm , and design a simple integration interface to achieve random pick and place. Using reinforcement learning technique, combined with remote center of motion control, training the robot to learn how to adjust the skew of the screw like the human wrist did.
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