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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 傅立成 | |
| dc.contributor.author | Guan-Hao Li | en |
| dc.contributor.author | 李貫豪 | zh_TW |
| dc.date.accessioned | 2021-06-15T02:37:25Z | - |
| dc.date.available | 2011-08-14 | |
| dc.date.copyright | 2009-08-14 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-08-12 | |
| dc.identifier.citation | [1] E. Garcia, et al., “The evolution of robotics research,” IEEE Transactions Robotics and Automation, Vol. 14, No. 1, pp. 90-103, March 2007.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44041 | - |
| dc.description.abstract | 在本篇論文裡，我們提出行為導向同步自我定位以及建立地圖(behavior-based Simultaneous Localization and Map building)的方法來處理以下輪型機器人(Wheeled Mobile Robot)於室內導航會遇到的問題：行為融合、量測以及數學建模的不確定性和機器人控制。行為導向之模糊邏輯軌跡規劃器(behavior-based fuzzy path planner) 藉由感測系統針對不同環境以及行為融合之間作出合理推論並且考慮多重控制目標：目標物趨近和安全導航的議題。一般而言，SLAM 解決量測誤差和機器人自我定位時發生的累積性誤差的問題。本篇研究不同於典型SLAM方法進一步考慮到數學建模誤差，應用理論方面的降階Kalman Filter (reduced-order KF) 於基於機器人導航滑動SLAM 的問題之中。因此，不確定性誤差每次都能夠有效地消除，而不用等到再次觀測到同一標的物才能夠消除。最後透過多次實驗，驗證所提出bSLAM的實驗成效。實驗結果顯示，比較SLAM 和bSLAM 兩種方法，發現平均誤差共變異量(error covariance) 在沿著牆走直線以及在複雜環境裡的兩次實驗場景裡，分別達到5.79% 和 26.6% 的改善率。 | zh_TW |
| dc.description.abstract | In this thesis, we propose a behavior-based Simultaneous Localization and Map building (bSLAM) approach to deal with the following navigation problem of a Wheeled Mobile Robot (WMR): the behavior fusion, the uncertainty from measurements and modeling and the WMR control. Considering the multiple control objects, i.e., goal approaching and navigation safety, the behavior-based fuzzy path planner is established to deal with the behavior fusion problem in associated with different interpretations of the environment from sensing system. Typically, the uncertainty of measurements together with the incremental error of the WMR self-localization is classified as the SLAM problem. In this research, we further consider the modeling uncertainty comparing with the SLAM problem so that the reduced-order SLAM is theoretically obtained via the variation approach in cope with the slipping and sliding effects. Therefore, the uncertainties are able to be effectively reduced at any motion time instead the time WMR revisits the well-known landmark in indoor environment. The effectiveness and the performance of the proposed bSLAM are verified via several experiments. The results which are compared with SLAM and bSLAM approach show the error covariance is averagely diminished from 5.79% to 26.6% along the corridor and in the complex environment, respectively. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T02:37:25Z (GMT). No. of bitstreams: 1 ntu-98-R95921002-1.pdf: 1698230 bytes, checksum: 6cfa3d8fefb63f250a60b88aa57af56a (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | 誌謝 I
摘要 II Abstract III Table of Contents IV List of Figures VI List of Tables IX 1 Introduction 1 1.1 Motivation 1 1.2 Related Researches 3 1.3 Contribution 5 1.4 Thesis Organization 6 2 Preliminaries 7 2.1 Problem Formulation 7 2.2 Theoretic Foundation of Estimation Theory 10 2.3 WMR Exploration Uncertainties 12 2.3.1 WMR Navigation in Precence of Uncertainty 12 2.3.2 EKF-SLAM Consistency Properties 14 2.4 WMR Ideal Mathematical Model 15 2.4.1 WMR Kinematics Model 15 2.4.2 EKF-SLAM Mathematical Model 16 3 Reduced-order EKF-SLAM Navigation 28 3.1 Behavior-based Path Planner Design 28 3.1.1 Relations between Behaviors and Energy Functions 29 3.1.2 Fuzzy Inference Behaviors and Energy Functions 33 3.2 WMR Trajectory Tracking Controller 38 3.3 Reduced-order EKF-SLAM Navigation with Sliding and Slipping effect 41 4 Experimental Results 46 4.1 WMR Navigation Uncertainty Estimation 47 4.2 Experimental Results on WMR Navigation 50 4.3 Experimental Results on bSLAM Navigation 57 5 Conclusions and Future Work 65 5.1 Conclusions 65 5.2 Future Work 65 References 67 | |
| dc.language.iso | en | |
| dc.title | 運用bSLAM修正輪型機器人室內導航之不確定性誤差 | zh_TW |
| dc.title | bSLAM Navigation of a Wheeled Mobile Robot in Presence of Uncertainty in Indoor Environment | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 王文俊,練光祐,簡忠漢,連豊力 | |
| dc.subject.keyword | 機器人控制、行為導向控制、同步自我定位及建立地圖, | zh_TW |
| dc.subject.keyword | Robot control, behavior-based control, SLAM, | en |
| dc.relation.page | 69 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-08-13 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位： | 電機工程學系 | |
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