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研究生:李俊則
研究生(外文):Lee, Chun-Tse
論文名稱:兼具視觸覺感知以及全驅動自適應機械手指實現機器人智慧操控之研究與開發
論文名稱(外文):Intelligent Robotic Manipulation Enabled by FASA Fingers and Visual-Tactile Perception
指導教授:張禎元
指導教授(外文):Chang, Jen-Yuan
口試委員:宋震國馮國華林沛群陳宗麟彭志誠
口試委員(外文):Sung, Cheng-KuoFeng, Guo-HuaLin, Pei-ChunChen, Tsung-LinPeng, Chih-Cheng
口試日期:2023-03-10
學位類別:博士
校院名稱:國立清華大學
系所名稱:動力機械工程學系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2023
畢業學年度:111
語文別:中文
論文頁數:180
中文關鍵詞:全驅動機構欠驅動機構擬人型夾爪動態靜力分析手眼校正視覺伺服控制點雲配對壓力感測器支援向量機影像物件辨識隨機堆疊料籃夾取基因演算法逆向運動學
外文關鍵詞:Fully-acutationunder-actuationanthropormorphic robotic handkinetostatic analysishand-eye calibrationvision servo controlpoint cloud registrationtactile sensorsupport vector machineimage object detectionrandom bin pickinggenetic algorithminverse kinematics
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近年來機器人憑藉其工作穩定性、商業化的價格以及成熟自動化技術逐漸走出工廠之外,開始融入於我們的生活當中,例如餐飲業自動化、飯店服務業、居家照護機器人等。不難發現機器人已從固定、單一的操作環境中,轉移至多變、未見過之環境中進行各式各樣的任務,為此本研究目標在於開發一套具感知擬人型機器人系統與其智慧操控策略應用,以面對泛用型的應用情境。本論文將涵蓋機器人系統的三種面向進行探究,分別為擬人型夾爪之機電整合、視觸覺系統之感測器整合、人工智慧技術之智慧操控。機電整合方面本論文提出兼具全驅動與自適應之擬人型夾爪設計,透過運動學分析以及動態靜力分析量化其運動表現,並以機電整合平台驗證其獨立關節運動性能與自適應包覆物體之能力。感測器整合方面,使用深度攝影機作為機器人系統感知外界之用,並開發適用於擬人機器人之快速手眼校正流程;觸覺感測方面開發磁場式三軸壓力感測器,以陣列式安裝擬人手指尖掌握局部資訊。智慧操控整合方面則是採用三種不同的人工智慧技術派別: 類比主義、連結主義以及進化主義,分別應用於物件重量預估、隨機物堆疊料籃夾取、多鏈共軛機械手之逆向運動學。
In recent years, robots have gradually entered our daily lives. It is easy to see that robots have moved from fixed operational environments to various and unseen environments to perform various tasks. Therefore, the goal of this research is to develop a human-like robotic system with perception and intelligent control strategies to face general scenarios. This dissertation will cover three aspects: mechatronics of a humanoid robotic hand, vision and touch sensor system, and intelligent robotic manipulation. First, this dissertation proposes the design of hybrid fully-actuated and self-adaptive mechanism for an anthropomorphic robotic finger. Its performance is quantified by kinematic analysis and kinetostatic analysis. Second, a stereo camera is employed in the humanoid robot, and a novel hand-eye calibration method is developed; as for tactile sensing, a magnetic type three-axis pressure sensor is developed and installed in the fingertips to perceive local information. Finally, three AI technologies are utilized for intelligent robotic manipulations, namely object weight estimation, random bin picking system, and inverse kinematics of multi-chain conjugate manipulators.
摘 要 I
Abstract II
誌謝 III
目錄 IV
圖目錄 VII
表目錄 XIII
第一章 緒論 1
1.1 前言 1
1.2 文獻回顧 3
1.2.1 擬人型機械手臂夾爪之發展 5
1.2.2 感測系統於機器人上之趨勢 10
1.2.3 機器人智慧操控決策之流派 16
1.3 研究問題與目標 20
1.3.1 研究問題 20
1.3.2 研究目標 21
第二章 兼具全驅動自適應擬人手指機電整合開發 23
2.1 文獻回顧與突破處 23
2.2 機構設計與數學模型建立 28
2.3 動態靜力分析與運動學分析 35
2.3.1 動態靜力分析 35
2.3.2 運動學分析 51
2.4 實驗架設與功能驗證 56
2.5 章節總結 64
第三章 基於視覺伺服控制之手眼校正流程開發 65
3.1 文獻回顧與突破處 65
3.2 新型態校正物設計與創新式手眼校正流程 73
3.2.1 新型態校正物設計 73
3.2.2 創新式手眼校正流程介紹 78
3.3 視覺伺服控制理論 83
3.3.1 應用於相機速度旋量之視覺伺服控制 83
3.3.2 應用於機械手臂速度旋量之視覺伺服控制 88
3.4 手眼校正演算法: 點雲配對 91
3.5 實驗架設與功能驗證 95
3.5.1 視覺伺服控制: 物件追蹤定位與機械手臂控制移動 95
3.5.2 手眼校正之絕對式精度誤差 99
3.6 章節總結 106
第四章 機器人智慧操控之研究與開發 107
4.1 陣列式三維觸覺感測器應用於物件重量估測 107
4.1.1 研究背景與問題定義 108
4.1.2 磁場感測式三維力量感測器與擬人夾爪整合開發 110
4.1.3 仿生式資料收集流程與支援向量機應用於重量評估 114
4.2 應用基因演算法解共軛多鏈逆向運動學 120
4.2.1 研究背景與問題定義 120
4.2.2 擬人手指工作空間分析 121
4.2.3 基因演算法與工作空間之改良 125
4.2.4 同時多指逆向運動學之運算 132
4.3 免除CAD模型之隨機堆疊物夾取系統開發 138
4.3.1 研究背景與問題定義 138
4.3.2 視覺影像辨識技術應用: Mask-rcnn 140
4.3.3 最佳夾取點策略與系統流程建立 144
4.3.4 隨機堆疊物夾取系統系統驗證實例 148
4.4 擬人機器人智慧操控技術整合 151
4.5 章節總結 156
第五章 結論與未來展望 157
附錄一 160
參考資料 167
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