Design and Implementation of Cognition Learning Algorithm for Humanoid Robot Playing 3 by 3 Square Baseball Game Using DBN and PSO

論文翻譯標題: 基於深度信賴網路和粒子群最佳化演算法之認知學習演算法設計實現人形機器人九宮格投球
  • 張 謙煜

學生論文: Master's Thesis


This thesis aims to design a cognition learning algorithm that allows the robot to learn the posture of playing 3 by 3 square baseball game The robot can hit the designated grid area accurately with this proposed algorithm The overall system proposed in this thesis includes image processing algorithm and learning algorithm In the image processing system a CMOS webcam sensor is used on the robot as the eye In order to catch the ball location efficiently two internet protocol cameras are installed on the top and side of the 3 by 3 square To recognize and track the objects a simple searching algorithm is developed for the issue Then a novel learning algorithm is motivated by a human thinking conception proposed in “Thinking Fast and Slow” by Daniel Kahneman He is a psychologist who won the Nobel Memorial Prize in Economic Science 2002 This algorithm is based on cognitive psychology which divides human thinking into two modes fast and slow The fast mode favors intuitive thinking while the slow mode favors rational thinking Furthermore we establish the fast mode by Deep Belief Network and the slow mode by Inertia Weight Particle Swarm Optimization Algorithm in the developed cognition learning algorithm The proposed algorithm is implemented and applied on the robot and then the robot performs the fast and slow mode in 3 by 3 square baseball game Finally experimental results demonstrate that the performance of the cognition learning method is very efficient In other words this learning algorithm also verifies that the thinking mode of the human being is reasonable and available on the robot
獎項日期2016 七月 25
監督員Tzuu-Hseng S. Li (Supervisor)