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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 郭重顯 | zh_TW |
| dc.contributor.advisor | Chung-Hsien Kuo | en |
| dc.contributor.author | 陳易宏 | zh_TW |
| dc.contributor.author | Yi-Hung Chen | en |
| dc.date.accessioned | 2025-09-17T16:09:23Z | - |
| dc.date.available | 2025-09-18 | - |
| dc.date.copyright | 2025-09-17 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2025-08-12 | - |
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Cao, "A Soft Piezoresistive Pressure Sensor Based on Porous Conductive CB/PDMS Composite," IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society, Singapore, Singapore, 2023, pp. 1-6, doi: 10.1109/IECON51785.2023.10311739. J. -Y. Lee , Y. -S. Seo, C. Park, J. -S. Koh, U. Kim, J. Park, H. Rodrigue, B. Kim and S. -H. Song, "Shape-Adaptive Universal Soft Parallel Gripper for Delicate Grasping Using a Stiffness-Variable Composite Structure," in IEEE Transactions on Industrial Electronics, vol. 68, no. 12, pp. 12441-12451, Dec. 2021, doi: 10.1109/TIE.2020.3044811. S. Naveen, S. Panigrahi, A. Vinit, I. H. Sudar and M. J. Thomas, "Development of Pneumatic Soft Gripper for Effective Material Handling," 2024 IEEE Recent Advances in Intelligent Computational Systems (RAICS), Kothamangalam, Kerala, India, 2024, pp. 1-6, doi: 10.1109/RAICS61201.2024.10690075. X. Wang, H. Kang, H. Zhou, W. Au, M. Y. Wang, and C. 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Burgard, "Improving Grid-based SLAM with Rao-Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling," Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, 2005, pp. 2432-2437, doi: 10.1109/ROBOT.2005.1570477. S. Kohlbrecher, O. von Stryk, J. Meyer and U. Klingauf, "A flexible and scalable SLAM system with full 3D motion estimation," 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics, Kyoto, Japan, 2011, pp. 155-160, doi: 10.1109/SSRR.2011.6106777. W. Hess, D. Kohler, H. Rapp and D. Andor, "Real-time loop closure in 2D LIDAR SLAM," 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016, pp. 1271-1278, doi: 10.1109/ICRA.2016.7487258. F. Dellaert, D. Fox, W. Burgard and S. Thrun, "Monte Carlo localization for mobile robots," Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C), Detroit, MI, USA, 1999, pp. 1322-1328 vol.2, doi: 10.1109/ROBOT.1999.772544. Min Cheol Lee and Min Gyu Park, "Artificial potential field based path planning for mobile robots using a virtual obstacle concept," Proceedings 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003), Kobe, Japan, 2003, pp. 735-740 vol.2, doi: 10.1109/AIM.2003.1225434. Y. Tian, Q. Ye, and D. Doermann, “YOLOv12: Attention-Centric Real-Time Object Detectors,” Feb. 2025, doi: 10.48550/arXiv.2502.12524. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99617 | - |
| dc.description.abstract | 本研究旨在開發可搭載於自主移動機器人之欠驅動機械手臂，並設計一具有四隻爪子之夾爪作為手臂之末端致動器。本研究使用之自主移動機器人為四舵輪機構，透過運動學的轉換，使其具備差速運動模式以及全向移動模式，並且具備里程計之回授。此外，自主移動機器人配備光學雷達以及慣性測量單元，並透過人工勢能場實現路徑規劃，使機器人能夠建置地圖並且導航及自主避障。經驗證，導航過程中最高時速可達每秒0.67公尺。此外，本研究開發兩種不同的欠驅動手臂，其均為三節串列式連桿機構，且透過拉線驅動使手臂運作，分別採用3D列印以及金屬製造。手臂上的每顆關節均配置絕對式磁編碼器，結合諧波減速機可實現高精度之位置控制，並且混合速度控制以及電流控制架構，實現響應快速且穩定的線驅動控制系統，實驗驗證各關節的平均誤差均小於0.2度，可滿足大多應用場合之需求。最後，本研究開發的軟式夾爪採用3D列印製成，並且透過線性軸承以及簡易四連桿機構使夾爪能以拉線方式驅動。各個爪子均為多材料之機構，使夾爪具有更好的物件輪廓順應性，此外，夾爪搭載多個感測器，結合物件辨識模型，可實現物件辨識、電流控制等功能。實驗證實透過物件辨識模型，夾爪可分辨不同種類的水果，並及時調整爪力進行物件夾取任務。 | zh_TW |
| dc.description.abstract | This study focuses on developing an underactuated manipulator mounted on an autonomous mobile robot (AMR) with a four-fingered gripper as its end effector. The AMR utilizes a four-steering-wheel mechanism to support both differential-drive and omnidirectional motion, providing odometer feedback. It is equipped with a 2D LiDAR and an inertial measurement unit (IMU), utilizing an artificial potential field approach for path planning, navigation, and obstacle avoidance. The robot achieved a maximum navigation speed of 0.67 m/s.
Two versions of the underactuated manipulator were designed, consisting of a three-link serial-chain mechanism driven by cables: one made from 3D printing and the other from metal. Each joint features an absolute magnetic encoder and a harmonic reducer for high-precision control, maintaining an average tracking error below 0.2°. A soft, four-fingered gripper was developed using 3D printing and a four-bar linkage for cable-driven actuation. Each finger is designed for improved contour compliance and includes sensors for real-time object detection and adaptive force control. Experimental results confirm the gripper can distinguish various types of fruit and adjust its grasp accordingly. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-09-17T16:09:23Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-09-17T16:09:23Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 中文摘要 iii 英文摘要 iv 目次 v 圖次 viii 表次 xiv 符號說明 xvi 第一章 緒論 1 1.1 研究背景與動機 1 1.2 文獻回顧 2 1.2.1 機械手臂之設計與應用 2 1.2.2 軟式夾爪之技術開發 2 1.3 論文架構 3 第二章 系統架構 4 2.1 系統架構與流程 4 2.1.1 系統架構圖 4 2.1.2 機器人作業系統Robot Operating System(ROS) 6 2.2 硬體設計與整合 7 2.2.1 機器人整體硬體架構 7 2.2.2 四舵輪自主移動機器人硬體架構 9 2.2.3 欠驅動機械手臂設計與硬體架構 14 2.2.3.1 第一代欠驅動機械手臂設計 14 2.2.3.2 第二代欠驅動機械手臂設計 23 2.2.4 軟式夾爪設計 33 第三章 機器人運動學 38 3.1 具四舵輪之自主移動平台車體運動學 38 3.1.1 四輪車輛運動學與兩輪車輛運動學之比較 38 3.1.2 轉向係數之優化 39 3.1.3 座標系定義 42 3.1.4 四舵輪車體運動學推導 42 3.1.4.1 當迴轉半徑R=±∞時的車體運動學推導 43 3.1.4.2 當迴轉半徑R≠±∞且R≠0時的車體運動學推導 44 3.1.4.3 當迴轉半徑R=0時的車體運動學推導 44 3.1.5 里程計推估 45 3.1.5.1 當θ>0°時之運動學計算 47 3.1.5.2 當θ<0°時之運動學計算 48 3.1.5.3 當θ=0°時之運動學計算 48 3.1.5.4 里程計之計算 48 3.1.6 線性速度及角速度與轉向係數和切線速度之轉換關係 49 3.1.6.1 直走、原地旋轉、或停止之轉換關係 50 3.1.6.2 車輛轉向時之轉換關係 50 3.2 欠驅動手臂運動學 52 第四章 機器人自主定位及導航之規劃及應用 54 4.1 機器人同時定位與地圖建置 54 4.2 人工勢場法之應用 55 第五章 欠驅動手臂及軟式夾爪之控制與應用 59 5.1 欠驅動手臂之控制流程 59 5.1.1 捲線系統之控制架構 60 5.1.2 控制器設計 61 5.2 軟式夾爪之控制架構 62 5.2.1 軟式夾爪控制器 62 5.2.2 電流檢測及濾波 63 5.3 影像蒐集及處理 64 5.4 物件辨識模型訓練及應用於夾爪力量調整 66 第六章 實驗結果與分析 68 6.1 自主移動平台之避障及導航驗證 68 6.1.1 自主避障驗證 69 6.1.2 自主導航驗證 74 6.2 欠驅動手臂定位實驗 76 6.3 軟式夾爪夾取實驗 79 第七章 結論與未來展望 82 7.1 結論 82 7.2 未來展望 83 參考文獻 84 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 自主移動機器人 | zh_TW |
| dc.subject | 欠驅動手臂 | zh_TW |
| dc.subject | 欠驅動機構控制 | zh_TW |
| dc.subject | 軟式夾爪 | zh_TW |
| dc.subject | 人工勢能場導航 | zh_TW |
| dc.subject | 物件辨識 | zh_TW |
| dc.subject | Underactuated Manipulator | en |
| dc.subject | Autonomous Mobile Robot | en |
| dc.subject | Object Detection | en |
| dc.subject | Artificial Potential Field for Navigation | en |
| dc.subject | Soft Gripper | en |
| dc.subject | Control of Underactuated Mechanisms | en |
| dc.title | 具軟式夾爪與欠驅動手臂之自主移動機器人設計及自主導航應用 | zh_TW |
| dc.title | Design and Application of an Autonomous Mobile Robot with a Soft Gripper and Underactuated Manipulator | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 黃漢邦;蘇順豐;傅立成 | zh_TW |
| dc.contributor.oralexamcommittee | Han-Pang Huang;Shun-Feng Su;Li-Chen Fu | en |
| dc.subject.keyword | 自主移動機器人,欠驅動手臂,欠驅動機構控制,軟式夾爪,人工勢能場導航,物件辨識, | zh_TW |
| dc.subject.keyword | Autonomous Mobile Robot,Underactuated Manipulator,Control of Underactuated Mechanisms,Soft Gripper,Artificial Potential Field for Navigation,Object Detection, | en |
| dc.relation.page | 88 | - |
| dc.identifier.doi | 10.6342/NTU202504199 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2025-08-14 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 機械工程學系 | - |
| dc.date.embargo-lift | N/A | - |
| 顯示於系所單位： | 機械工程學系 | |
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