隨著科技發展引領產業轉型，生活中被大量引入機械手臂作為智慧自動化的應用，可以從事高重複性或是高風險的工作任務。其中機器手作為與外界互動的不可或缺的部分，在應用上相當重要。在現今的世界中，各式各樣的機器手已然出現在各領域中。在工業方面，由於過往的商業模式是以大量生產的方式來降低製造成本，因此在考量穩定夾取的可靠度上，末端效應器的結構都是針對特定的物體或用途來設計，不同情境下需要不斷更換。然而工業4.0提出智慧工廠的概念，其最重要的目標是滿足現今市場對於商品新穎、獨具特色的要求，可以達到產品高度客製化，這將完全顛覆傳統工廠的生產方式。
為了符合多樣化的生產需求，本研究將對於多功能機器手進行研究來增加單一機器手的實用性，研究內容分為三個部分，首先是開發具有兩種夾取手段的機器手機構，整合兩種夾取手段可以使機器手應付更多元的工作環境。第二部分是設計夾持穩定性的分析流程，並運用基因演算法進行機構最佳化的分析，來提升機器手夾持能力。最後，在兩種夾取手段的搭配與視覺伺服的概念下，實現欠驅動機器手對於物體的精準操控任務。

As technology advances, leading industrial transformation, robotic system have been introduced in large numbers as an application of intelligent automation, which can engage in highly repetitive or high-risk tasks. Robotic hands play an indispensable role of robotic system in the interaction with the surroundings. In the industrial sector, as traditional business models have focused primarily on mass production to reduce manufacturing costs, the structure of end effectors has been tailored to specific objects or purposes and modified for different contexts. However, Industry 4.0 proposes the concept of intelligent factories, aiming to meet the market's demand for novel and unique products and to achieve a high degree of product customization. This concept completely revolutionized the traditional manufacturing methods of factories.
To meet diverse manufacturing demands, this thesis investigates the multifunctional robotic hands to enhance the practicality of a single robotic hand. This research comprises three main parts. The first part is to develop a robotic hand with two grasping modalities and it enables the robot to cope with more diversified working environments. The second part is to design the analysis process of grasping stability and apply the genetic algorithms for the optimal analysis of the mechanism to improve the grasping ability of the robotic hands. Finally, with the combination of the two grasping modalities and the concept of visual servo control, precise in-hand manipulation with underactuated robotic hand is realized.

摘要 I
Abstract II
致謝 III
目錄 IV
圖目錄 VIII
表目錄 XII
符號說明 XIII
第一章 緒論 1
1.1 前言 1
1.2 研究動機 2
1.3 文獻回顧 3
1.3.1 機器手機構 3
1.3.2 夾持最佳化分析 15
1.3.3 操控方法 16
1.4 研究目標 18
1.5 研究方法 19
第二章 理論背景 21
2.1 前言 21
2.2 欠驅動手指力學模型 21
2.3 基因演算法 32
2.3.1 基因演算法專有名詞 32
2.3.2 基因演算法計算流程 33
2.3.3 基因演算法優勢 36
2.4 章節總結 37
第三章 機器手機構設計 38
3.1 前言 38
3.2 機器手介紹 38
3.2.1 機器手機構 38
3.2.2 手指機構與運動學 42
3.2.3 伸縮吸盤功能 45
3.2.4 兩種夾取手段搭配 48
3.3 章節總結 49
第四章 機器手夾持穩定性分析 50
4.1 前言 50
4.2 夾持穩定性 50
4.2.1 抓取穩定性 50
4.2.2 抓握穩定性 53
4.3 分析方法設計 53
4.3.1 量化指標計算流程 53
4.3.2 模擬分析結果 59
4.4 實驗架設與驗證 62
4.5 機器手機構參數分析 66
4.5.1 手指開合角度範圍分析 66
4.5.2 手指長度分析 68
4.6 機器手機構參數最佳化 71
4.6.1 機構參數改變之量化指標計算流程 71
4.6.2 基因演算法最佳化機構參數 73
4.7 章節總結 76
第五章 機器手操控系統建立 77
5.1 前言 77
5.2 操控任務描述 77
5.3 實驗架設 79
5.4 操控方法 81
5.4.1 致動器動作集設計 81
5.4.2 視覺伺服理論 84
5.5 實驗驗證 86
5.5.1 動作集穩定性 86
5.5.2 動作集關係式 86
5.5.3 控制參數調整 87
5.6 章節總結 89
第六章 結論與未來展望 90
6.1 結論 90
6.2 未來展望 91
參考文獻 93

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