本論文主旨在設計與實現機器手臂抓取、移動及置放水杯之智慧型控制策略。首先，介紹本論文所研製之五自由度機器手臂，並詳述其機構設計概念及其控制系統架構。此外，機器手臂之順向運動學與逆向運動學推導也詳述於文中。實驗過程中機械手臂必須於固定時間內抓取並移動裝了近乎全滿之水杯，若速度曲線規劃不佳導致夾爪姿勢無法維持水平姿態，或是加速度過大，杯中的液體將會溢出。為了解決上述問題，本論文使用加速度計及陀螺儀以精確得知機器手臂在移動中之加速度以及夾爪姿態等資訊，再將其讀值回傳電腦，並由智慧型控制策略進行學習。智慧型控制策略使用之演算法為適應性慣性權重與加速度係數粒子群演算法(AIWCPSO)，經歷多次學習之後，機械手臂即能規劃出每顆關節點之馬達速度曲線，並將此速度曲線套用於機器手臂，使其夾爪維持水平姿勢不過度傾斜或加速度過大，讓水免於溢出水杯。最後，經由三個不同路徑進行置放水杯實驗，證實智慧型控制策略應用於機器手臂之速度規劃是具體可行性的。

This thesis proposes an intelligent control strategy such that a robot arm is capable of picking and placing cups without spilling out the contained water. First, the system architecture of a 5-DOF robot arm and its design concept of mechanism are introduced. Second, both the forward and inverse kinematics of the robot arm are derived. By the setup of experiment, the designed and implemented robot arm will grasp a cup of water and move it to another place. However, if the acceleration or the orientation of the robot arm are inappropriate, water in the cup may be spilt out during the movement. Therefore, the inertial measurement unit (IMU) is used for obtaining the related information. According to the obtained information, the velocity curves of each joint can be optimized by Adaptive Inertia Weight and Acceleration Coefficients Particle Swarm Optimization (AIWCPSO). Finally, the experimental results demonstrate the feasibility and effectiveness of the proposed method.

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