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系統識別號 U0026-2212201615195900
論文名稱(中文) 基於適應性粒子群體最佳化演算法之居家服務型機器人手臂避障與抓取姿態控制之設計與實現
論文名稱(英文) Design and Implementation of Obstacle Avoidance and Grasping Posture Control of Arm for Home Service Robot by Adaptive Particle Swarm Optimization Algorithms
校院名稱 成功大學
系所名稱(中) 電機工程學系
系所名稱(英) Department of Electrical Engineering
學年度 105
學期 1
出版年 105
研究生(中文) 林摯睿
研究生(英文) Chih-Jui Lin
學號 N28981117
學位類別 博士
語文別 英文
論文頁數 66頁
口試委員 指導教授-李祖聖
召集委員-黃國勝
口試委員-蔡清池
口試委員-杜國洋
口試委員-郭重顯
口試委員-陳中政
口試委員-莊智清
口試委員-鄭銘揚
口試委員-王振興
中文關鍵字 居家服務型機器人  機械手臂  智慧型演算法  避障  粒子群體最佳化演算法  人工蜂群演算法 
英文關鍵字 Artificial bee colony  home service robot  intelligent algorithm  obstacle avoidance  particle swarm optimization  robotic arm 
學科別分類
中文摘要 本論文主要探討居家服務型機器人機械手臂避障與抓取姿態控制法之設計與實現。居家服務型機器人之機械手臂在進行手臂移動至目標點任務時,機械手臂的每一顆馬達都必需轉動到適合的角度,本論文使用粒子群體最佳化演算法進行每一顆馬達轉動角度之規劃,在手臂避障控制方面透過提出的改良之適應性粒子群體最佳化演算法,且搭配考慮到在具有障礙物環境之下的避障能力所設計的適應性函數,達到手臂避障控制之效果。此外由於機械手臂進行抓取任務時,除了需要考慮目標物的空間座標位置之外還必須要搭配合適的抓取姿態才能夠順利的抓取目標物,本論文提出改良之適應性粒子群體最佳化演算法搭配人工蜂群演算法中之偵查蜂的概念應用於機械手臂抓取姿態之控制,達到手臂抓取姿態控制之效果。最後,透過實驗結果顯示本論文提出之智慧型演算法具可行性與實用性。
英文摘要 This dissertation focuses on obstacle avoidance when moving a robot arm to an object and the grasping posture control design for a home service robot. Each motor on the robotic arm must be able to rotate to the appropriate degree when moving the robotic arm to the object task of the home service robot. This dissertation employs a particle swarm optimization (PSO) algorithm to calculate each motor’s degree of rotation. In the section concerning obstacle avoidance, the dissertation proposes an improved adaptive PSO algorithm with a fitness function that works under the obstacle environment to achieve a robotic arm obstacle avoidance design. On the other hand, the grasping task of the robotic arm not only considers the object coordinate position but also cooperates with the appropriate grasping posture. This dissertation proposes an improved adaptive PSO algorithm using the scout bee behavior identified in the artificial bee colony algorithm and applies it to improve the robotic arm grasping posture control design. Finally, the experimental results show the feasibility and practicality of the proposed intelligent algorithm.
論文目次 Contents

Abstract(Chinese) I
Abstract(English) II
Acknowledgment(Chinese) III
Contents IV
List of Figures VI
List of Tables VIII


Chapter 1. Introduction 1
1.1 Motivation and Literature Survey 1
1.2 Dissertation Organization 5

Chapter 2. Position and Orientation of 6-DOF Robotic Arm
7
2.1 Introduction 7
2.2 Robotic Arm Kinematic Analysis 9
2.3 Grasp Orientation Analysis 12

Chapter 3. Integrated PSO Algorithm based Obstacle Avoidance Analysis Design 15
3.1 Introduction 15
3.2 Various PSOs and the proposed PSO algorithm 16
3.2.1 Various PSOs 16
3.2.2 PSO-A 18
3.2.3 PSO-IA, PSO-AC and PSO-IAC 19
3.2.4 Fitness Function for The Obstacle Avoidance Problem
21
3.3 Experimental Results 22
3.3.1 Experimental Setup 22
3.3.2 Free-Space State 25
3.3.3 Obstacle Avoidance State 28

Chapter 4. Grasping Pose Analysis Design using ABC based Adaptive PSO 33
4.1 Introduction 33
4.2 Artificial Bee Colony and Proposed AIWCPSO-S Algorithms 34
4.2.1 ABC and GABC 34
4.2.2 AIWCPSO and AIWCPSO-S 38
4.2.3 Fitness Function for Grasping Analysis 43
4.3 Experimental Results 45
4.3.1 Experimental Setup 46
4.3.2 Simulation Results 48
4.3.3 Real-Time Experiments 52

Chapter 5. Conclusions and Future Works 55
5.1 Conclusions 55
5.2 Future Works 56

References 58
Publication List 64
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