臺灣博碩士論文加值系統

機械手臂以往都是以人工規劃作為移動時之路徑規劃方式，但是在複雜的環境下，人工規劃是無法滿足實際需求，因此，讓機械手臂能自行搜索出路徑，既能節省人力也能滿足即時避障的功能。
本文將平面運動二自由度機械手臂及三維空間運動三自由度機械手臂作為研究對象，分別對其做運動學分析及推導出運動方程式。接著，利用人工位能場法對其做路徑規劃，然而在傳統人工位能場法中，其吸引力位能場函數之參數通常使用試誤法來找出，也有學者是透過基因演算法找出，但這些方法都需要大量的計算，不容易找出，而排斥力位能場則是將障礙物視為一個點，並不符合實際情況。因此，本文對傳統人工位能場法進行修改，將透過設定阻尼比及安定時間求出吸引力位能場函數之參數，便可大大減少了計算量，同時也修改了排斥力位能場函數，將其從點的避障變為圓狀或球狀的避障，並利用分區控制方案的方式及修改後的人工位能場法設計了控制器，所設計出的控制器具有強健性，即使機械手臂的規格改變，所規劃出的路徑也不會改變。
最後，透過增加虛擬目標點來改善傳統人工位能場法中局部最小值的問題，使其能避開障礙物也能精準到達所要求的位置，並在MATLAB上進行模擬驗證。

In the past, the manipulator was manually planned to make the path planning method when moving. However, in a complicated environment, the manual planning could not satisfy the actual needs. Therefore, let the manipulator search for the path by itself, can economize manpower and satisfy real-time obstacle avoidance.
In this paper, the two-degree-of-freedom manipulator of plane motion and the three-degree-of-freedom manipulator of three-dimensional motion are taken as research objects, and kinematics analysis and motion equation are respectively derived. Then, using the artificial potential field method to do path planning, in the traditional artificial potential field method, the parameters of the attractive potential field function are usually found by try and error, and some scholars find through by the genetic algorithm. But these methods require a lot of calculations, wich are not east to find, and the repulsive potential field let the obstacle as a point, which is not in line with the actual situation. Therefore, in this paper, the traditional artificial potential field method is modified, and the parameters of the attractive potential field function can be obtained by setting the damping ratio and the settling time, which can greatly reduce the calculation, the obstacle in repulsive potential field function is also modified to change from a point to spherical. And the controller is designed by the method of the partition control scheme and the modified artificial potential field method. The designed controller is robust,even if the specifications of the manipulator change, the planned path will not change.
Finally, by adding virtual target points to improve the local minimum problem, it can avoid the obstacles and reach the required position accurately, and simulate in MATLAB.

誌　謝 i
摘　要 ii
Abstract iii
目　錄 iv
圖目錄 vii
表目錄 ix
第一章 緒論 1
1.1 前言 1
1.2 文獻回顧 2
第二章 運動分析及運動方程式 6
2.1 座標系統 7
2.1.1 平面運動二自由度機械手臂之座標系統 8
2.1.2 三維空間運動三自由度機械手臂之座標系統 9
2.2 順向運動學 10
2.2.1 平面運動二自由度機械手臂之順向運動學 10
2.2.2 三維空間運動三自由度機械手臂之順向運動學 11
2.3 運動方程式 13
2.3.1 平面運動二自由度機械手臂之運動方程式 14
2.3.2 三維空間運動三自由度機械手臂之運動方程式 17
2.4 空間轉換 22
2.4.1 平面運動二自由度機械手臂之雅可比矩陣 23
2.4.2 三維空間運動三自由度機械手臂之雅可比矩陣 24
第三章 機械手臂路徑規劃 25
3.1 人工位能場法 25
3.1.1 吸引力位能場 26
3.1.2 排斥力位能場 26
3.2 虛擬目標點 28
3.3 控制器設計 29
3.3.1 修改型吸引力控制器 30
3.3.2 虛擬目標點吸引力控制器 30
3.3.3 修改型排斥力控制器 31
3.3.4 參數推導 31
3.3.5 完整系統架構 33
第四章 模擬結果 34
4.1 工作空間無障礙物 34
4.1.1 模擬一：平面運動二自由度機械手臂 34
4.1.2 模擬二：三維空間運動三自由度機械手臂 38
4.2 工作空間有障礙物 44
4.2.1 模擬三：平面運動二自由度機械手臂 44
4.2.2 模擬四：三維空間運動三自由度機械手臂 49
第五章 結論與未來展望 58
5.1 結論 58
5.2 未來展望 59
參考文獻 60
附錄 62
A 三維空間運動三自由度機械手臂之運動方程式 62
B 三維空間運動三自由度機械手臂之雅可比矩陣 63

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