臺灣博碩士論文加值系統

目前機器手臂已成功地應用在自動化產線上，但無論是何種機器手臂，在快速運轉過程中，會有多次加速度和減速的情形。而為了控制機器手臂末端點於空間之變化，必須利用軌跡規劃來產生機器手臂的移動軌跡，使位置、速度與加速度具平滑特性。
為了提高製造生產率和運動穩定性，要如何在相同的起點與終點的前提下，使該軌跡足夠平滑以避免過大的機械震動，並且在滿足運動學約束下盡可能的減少花費時間，是重要的課題。本文提出一個基於基因演算法的機器人軌跡規劃方法，首先將手臂末端點狀態經過逆向運動學轉換到關節狀態，再利用基因演算法求出機器人的最佳運行時間。
本文利用現有機械手臂的D-H模型，對其進行不同的軌跡規劃，並使用五次多項式內插值，對所有的關節節點進行計算求得來機器人的運行軌跡。再由基因演算法來找出時間最優化的軌跡規劃。
根據實驗結果發現，本方法在速度、加速度和急跳度(Jerk)的約束下，可以使機器人末端點的運行軌跡平滑，時間最優化，可做為機器手臂軌跡規劃時間分配之參考。

According to the increased demand for the automated production line, the manipulator has been successfully applied to automated production lines. However, no matter what kind of manipulator, there will be multiple accelerations and decelerations during moving fast, and in order to control the change of position and attitude of the manipulator in space, and to make the position, speed and acceleration have smooth characteristics, it is necessary to use the trajectory planning to generate the movement trajectory of the manipulator.

In order to improve manufacturing productivity and stability of motion. It is an important issue that gives the overall optimal time trajectory planning under the premise of the same starting point and end point.
The study posed a method that trajectory planning of the manipulator based on genetic algorithm.
Firstly, the state of the end point of the arm is transformed into the joint state through inverse kinematics, and then the optimal running time of the robot is obtained by using the genetic algorithm.
In this paper, the D-H model of the existing manipulator is used to carry out different trajectory planning, and the quintic polynomial interpolation is used to calculate the running trajectory of the manipulator. Then the genetic algorithm is used to find the optimal time trajectory planning.
According to the experimental results, the method can smooth the running track of the manipulator end point and optimize the time under the constraints of speed, acceleration and jerk.

摘要...i
Abstract...iii
誌謝...v
目錄...vi
表目錄...viii
圖目錄...ix
符號說明...x
第一章 緒論...1
1.1 前言...1
1.2 動機與目的...1
1.3 文獻回顧...2
1.4 論文架構...3
第二章 研究方法...4
2.1 研究步驟...4
2.2 機器手臂的數學模型...5
2.2.1順向運動學...5
2.2.2 軌跡規劃...6
2.2.3軌跡規劃的邊界約束...9
2.3 基本假設...11
2.4 限制條件...11
2.5 適應函數...12
2.6 基因演算法模組設計...14
第三章 實驗結果與討論...16
3.1 軌跡一...16
3.2 軌跡二...23
3.3 軌跡三...29
第四章 結論與未來展望...35
4.1 結論...35
4.2未來展望...35
參考文獻...36
Extended Abstract...38

[1]F. Forster, 2006, "A high-resolution and high accuracy real-time 3D sensor based on structured light," in Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission, 208-215.
[2]D. Baek, S. Cho and H. Bang, 2014, "Wheel alignment inspection by 3D point cloud monitoring," Journal of Mechanical Science and Technology, 28 (4), pp. 1465-1471.
[3]D. Knowles, 2007,"oday's technician –shop manual for automotive suspension & steering systems, Fourth ed. New York", USA: Thomson Delmar Learning.
[4]K.Shin,N. McKay, 1986, " A dynamic programming approach to trajectory planning of robotic manipulators "Auto .Control .IEEE Trans,31,pp491-500.
[5]K S Fu, Ralph Gonzalez, C S G Lee,1987, Robotics: Control Sensing. Vis.
[6]J Xiong X Xu X Zhao, 2014, " Research on trajectory-planning based on genetic algorithms for SCARA robot Guidance Navigation and Control Conference (CGNCC) IEEE Chinese pp. 1321-1324.
[7]X Liao W Wang Y Lin, 2010, "Time-optimal trajectory planning for a 6R jointed welding robot using adaptive genetic algorithms" Computer Mechatronics Control and Electronic Engineering (CMCE) 2010 International Conference on vol. 2 pp. 600-603.
[8]X Jin J Kang J Zhang, 2016, "Trajectory Planning of a Six-DOF Robot Based on a Hybrid Optimization Algorithm" Computational Intelligence and Design (ISCID) 2016 9th International Symposium on vol. 2 pp. 148-151.
[9]Speed B. Nike, 2001 "Robotics Analysis System Application" Pearson Education, Vol.2,5 pp .29~85,147~170.
[10]Y.S. Xia, J. Wang, 2001, "A dual neural network for kinematic control of redundant robot manipulators", IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), vol. 31, no. 1, pp. 147-154, Feb.
[11]H.C. Huang, C.P. Chen, P.R. Wang, 2012, "Particle swarm optimization for solving the inverse kinematics of 7-DOF robotic manipulators", 2012 IEEE International Conference on Systems Man and Cybernetics (SMC), pp. 3105-3110.
[12]Francisco J. Rubio, 2009, "Simultaneous algorithm to solve the trajectory planning problem "Mechanism and Machine Theory 44, pp 1910-1922.
[13]Francisco Valero, 2006, "Trajectory planning in Workspaces with obstacles taking into the dynamic robot behavior" Mechanism and Machine Theory 41, pp525-536.
[14] T. Chettibi, 2004, "Minimum cost trajectory planning for industrial robots" European Journal of Mechanics A/Solids 23, pp 703-715.
[15]R.P. Paul and H. Zong, 1984, "Robot Motion Trajectory Specification and Generation", International Symposium on Robotics Research, Kyoto, Japan.
[16]Denavit, Jacques; Hartenberg, Richard Scheunemann (1955). "A kinematic notation for lower-pair mechanisms based on matrices". Trans ASME J. Appl. Mech. 23: 215–221