博碩士論文 107552013 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:26 、訪客IP:3.236.156.34
姓名 林顯逢(Hsien-Feng Lin)  查詢紙本館藏   畢業系所 資訊工程學系在職專班
論文名稱 基於光達和九軸運動感測器融合的SLAM
(SLAM Based on Fusion with LiDAR and 9-Axis Motion Sensor)
相關論文
★ 整合GRAFCET虛擬機器的智慧型控制器開發平台★ 分散式工業電子看板網路系統設計與實作
★ 設計與實作一個基於雙攝影機視覺系統的雙點觸控螢幕★ 智慧型機器人的嵌入式計算平台
★ 一個即時移動物偵測與追蹤的嵌入式系統★ 一個固態硬碟的多處理器架構與分散式控制演算法
★ 基於立體視覺手勢辨識的人機互動系統★ 整合仿生智慧行為控制的機器人系統晶片設計
★ 嵌入式無線影像感測網路的設計與實作★ 以雙核心處理器為基礎之車牌辨識系統
★ 基於立體視覺的連續三維手勢辨識★ 微型、超低功耗無線感測網路控制器設計與硬體實作
★ 串流影像之即時人臉偵測、追蹤與辨識─嵌入式系統設計★ 一個快速立體視覺系統的嵌入式硬體設計
★ 即時連續影像接合系統設計與實作★ 基於雙核心平台的嵌入式步態辨識系統
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 (2025-6-30以後開放)
摘要(中) 光達 (LiDAR) 是近年來受到矚目的一種 SLAM 技術,原因是它具有高量測距離、高精度、高辨識度等優點,可滿足自主行動機器人 SLAM 的需求。但 LiDAR 存在的問題是它的製造工藝困難且調校費時不易被大量生產,導致價格居高不下,而影響了 SLAM 系統的應用推廣。有鑑於當前許多學術論文或市售產品用於 SLAM 的方法和技術,多數是基於使用LiDAR及各自開發的演算法來實現,這除了提高產品的成本之外也大幅增加系統開發者的研發週期。
本研究以 MIAT 方法論設計了一個低成本且高效能的 LIF-SLAM 系統,它是基於一個低成本的距離感測器陣列和一個低成本的九軸姿態感測器,利用它們融合的互補特性來提升整個系統的SLAM建圖性能,同時在開源軟體 ROS 中選用穩健性最高、且能構建具有最小誤差地圖的 cartographer SLAM 演算法來整合至本系統,以縮短系統開發者的研發週期。
在系統整合實驗中,LIF-SLAM 系統生成的SLAM地圖與 ground truth 誤差僅為 2.3829%,而市售產品 Neato XV-11 系統的誤差為 33.6774%,該結果顯示本系統具有更好的建圖性能且更貼近真實世界中的場景。本研究證明了 LIF-SLAM 系統在室內局部空間範圍小於4米的條件下,能夠替代 LiDAR 作為環境探勘和姿態定位的硬體裝置,且預期可大幅降低製造工藝和調校上的難度,也不需要嚴苛的組裝環境,具有更佳的使用壽命,同時也縮短了系統開發者對產品的研發週期。
摘要(英) Light detection and ranging (LiDAR) is a simultaneous localization and mapping (SLAM) technology that has attracted considerable research attention in recent years. LiDAR, which has the advantages of a long detection distance, high precision, and high recognition, satisfies the SLAM needs of autonomous mobile robots. However, LiDAR is costly because of manufacture difficulties and the requirement of time-consuming adjustments. These drawbacks hinder the mass production of LiDAR devices and thereby affect the application and promotion of SLAM systems. Various researchers have used LiDAR and self-developed algorithms to realize SLAM. This method considerably increases the length of the research and development cycle in system development.
This study used the MIAT methodology to design a low-cost and high-performance LIF-SLAM system based on a low-cost distance sensor array and low-cost nine-axis posture sensor. This system was combined with the cartographer SLAM algorithm in the ROS open-source software. The adopted methodology considerably decreased the research and development cycle in system development.
The results of the system integration experiment revealed that the LIF-SLAM system generated a SLAM map with an error of only 2.3829% compared with the ground truth (the error of the Neato XV-11 system was 33.6774%). The designed LIF-SLAM system provides high SLAM performance in real-world environments. This study indicates that the designed system can replace LiDAR as a hardware environmental exploration device in an indoor space with a range of less than 4 m. The designed system substantially reduces the difficulties in the manufacturing process and adjustments. It does not require a rigorously controlled assembly environment and exhibits a relatively high usage lifespan and mapping performance; thus, the product research and development period required by system developers is shortened.
關鍵字(中) ★ 光達
★ 距離感測器陣列
★ 九軸運動感測器
★ 機器人作業系統
★ cartographer SLAM
★ MIAT方法論
關鍵字(英) ★ LiDAR
★ Distance sensor array
★ Nine-axis motion sensor
★ ROS
★ cartographer SLAM
★ MIAT methodology
論文目次 中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
圖目錄 viii
表目錄 xii
一、緒論 1
1-1 研究動機 1
1-2 研究目的 2
1-3 論文架構 3
二、技術回顧 4
2-1 光達 (LiDAR) 4
2-2 九軸運動姿態與室內定位 6
2-3 SLAM 11
2-4 感測器融合 14
三、LiDAR/IMU融合SLAM系統 18
3-1 LIF-SLAM系統架構 18
3-2 距離感測陣列子系統 19
3-2-1 系統初始化程序 20
3-2-2 感測器校正程序 21
3-2-3 空間資訊採集程序 21
3-3 九軸姿態感測子系統 22
3-3-1 系統初始化程序 22
3-3-2 感測器姿態校準程序 22
3-3-3 感測器融合程序 30
3-4 控制單元 31
3-5 SLAM單元 34
四、LIF-SLAM系統設計 36
4-1 LIF-SLAM系統設計 36
4-2 距離感測陣列子系統設計 37
4-2-1 系統初始化設計 39
4-2-2 感測器校正設計 40
4-2-3 空間資訊採集設計 41
4-3 九軸姿態感測子系統設計 43
4-3-1 感測器校準設計 44
4-3-2 感測器融合設計 45
4-4 控制單元設計 47
4-5 SLAM單元設計 48
4-6 軟體合成與驗證 49
五、系統整合驗證與實驗 52
5-1 實驗平台與工具 52
5-1-1 微控制器平台 52
5-1-2 距離感測器模組 53
5-1-3 伺服馬達 54
5-1-4 直流降壓器模組 55
5-1-5 慣性感測器模組 56
5-1-6 磁力計模組 57
5-1-7 軟體開發工具 58
5-2 系統功能方塊驗證 61
5-2-1 距離感測陣列子系統功能驗證 61
5-2-2 九軸姿態感測子系統功能驗證 63
5-2-3 控制單元功能驗證 68
5-2-4 SLAM單元功能驗證 69
5-3 系統整合驗證 72
5-4 討論 76
六、結論與未來展望 77
6-1 結論 77
6-2 未來展望 78
參考文獻 79
參考文獻 [1] M.W.M.G. Dissanayake, P. Newman, S. Clark, H.F. Durrant-Whyte, M. Csorba, “A solution to the simultaneous localization and map building (SLAM) problem,” IEEE Transactions on Robotics and Automation, vol. 17, no. 3, pp. 229-241, 2001
[2] Rauf Yagfarov, Mikhail Ivanou, Ilya Afanasyev, “Map Comparison of Lidar-based 2D SLAM Algorithms Using Precise Ground Truth,” 2018 15th International Conference on Control Automation Robotics and Vision (ICARCV), pp. 1979-1983, 18-21 Nov. 2018, Singapore, Singapore
[3] Jingyun Liu, Qiao Sun, Zhe Fan, Yudong Jia, “TOF Lidar Development in Autonomous Vehicle,” 2018 IEEE 3rd Optoelectronics Global Conference (OGC), pp. 185-190, 4-7 Sept. 2018, Shenzhen, China
[4] Arthur Huletski, Dmitriy Kartashov, Kirill Krinkin, “VinySLAM: An indoor SLAM method for low-cost platforms based on the Transferable Belief Model,” 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 6770-6776, 24-28 Sept. 2017, Vancouver, BC, Canada
[5] Zheng Gong, Jonathan Li, Wei Li, “A low cost indoor mapping robot based on TinySLAM algorithm,” 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 4549-4552, 10-15 July 2016, Beijing, China
[6] Wolfgang Hess, Damon Kohler, Holger Rapp, Daniel Andor, “Real-time loop closure in 2D LIDAR SLAM,” 2016 IEEE International Conference on Robotics and Automation (ICRA), pp. 1271-1278, 16-21 May 2016, Stockholm, Sweden
[7] David Tedaldi, Alberto Pretto, Emanuele Menegatti, “A robust and easy to implement method for IMU calibration without external equipments,” 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 3042-3049, 31 May-7 June 2014, Hong Kong, China
[8] Joao Machado Santos, David Portugal, Rui P. Rocha, “An evaluation of 2D SLAM techniques available in Robot Operating System,” 2013 IEEE International Symposium on Safety Security and Rescue Robotics (SSRR), pp. 1-6, 21-26 Oct. 2013, Linkoping, Sweden
[9] Andrea Censi, “An ICP variant using a point-to-line metric,” 2008 IEEE International Conference on Robotics and Automation, pp. 19-25, 19-23 May 2008, Pasadena, CA, USA
[10] M. Euston, P. Coote, R. Mahony, R. Jonghyuk Kim, T. Hamel, “A complementary filter for attitude estimation of a fixed-wing UAV,” 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 340-345, 22-26 Sept. 2008, Nice, France
[11] P. Biber, W. Strasser, “The normal distributions transform: a new approach to laser scan matching,” Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat No 03CH37453), vol. 3, pp. 2743-2748, 27-31 Oct. 2003, Las Vegas, NV, USA, USA
[12] V. Dupourque, “A robot operating system,” Proceedings 1984 IEEE International Conference on Robotics and Automation, pp. 342-348, 13-15 March 1984, Atlanta, GA, USA, USA
[13] D.K. Killinger, “Lidar (light detection and ranging),” Laser Spectroscopy for Sensing, pp. 292-312, 2014
[14] Kin Leong Ho, Paul Newman, “Loop closure detection in SLAM by combining visual and spatial appearance,” Robotics and Autonomous Systems, vol. 54, no. 9, pp. 740-749, 2006
[15] Yu-Li Yang, “9-Axis Motion Sensor Fusion and Its Applications,” Department of Computer Science & Information Engineering, National Central University, 2012
[16] Jheng-Yu Yang, The core equipment of self-driving cars-LiDAR development trend, 2018 [Online]. Available: https://mic.iii.org.tw/industry.aspx?id=308&list=1
[17] LiDAR’s principle [Online]. Available: https://www.slamtec.com/cn/News/Detail/316
[18] Inertial Sensor Noise Analysis Using Allan Variance [Online]. Available: https://www.mathworks.com/help/nav/ug/inertial-sensor-noise-analysis-using-allan-variance.html
指導教授 陳慶瀚 審核日期 2020-6-24
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明