The purpose of this thesis is to study and develop intelligent agents for the forthcoming Space Station Freedom. Relevant intelligent capabilities, which are necessary in a semi-autonomous laboratory environment, are assumed to be built into a robot. An intelligent controller based on the DEVS formalism and the event-based approach is considered for an experiment. We shall discuss multiple model representations, where each model is tailored toward a specific purpose. Considering the necessity of diagnostic capabilities, we shall discuss the possibility of hierarchical diagnostic units for the Space Station. A high-level diagnostic unit is implemented on the basis of an artificial intelligence scheme and a hierarchy of diagnosers. This thesis also discusses the need for real-time diagnostic units and real-time data acquisition. We shall consider a constraint driven diagnostic unit which utilizes the time/cost (i.e., the actual associated cost or time in inquiring information necessary for a diagnosis process) criterion in an attempt to locate the cause(s) of failures.

Fung Wai-keung. / "February 5, 2001." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (p. 109-116). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Localization is one of the most difficult and costly problems in mobile robotics. Vision and odometry/AHRS (Attitude and Heading Reference System, three axial gyroscopes, accelerometers and magnetometers) sensors fusion strategy is prevalent in the recent years for the robot localization, due to its low cost and effectiveness in GPS-denied environments. In this thesis, a new adaptive estimation algorithm is proposed to estimate the robot position by fusing the monocular vision and odometry/AHRS sensors, and utilizing the properties of perspective projection. By the new method, the robot can be localized in real time in the GPS-denied and mapless environments, and the localization results can be theoretically proved convergent to their real values. Compared to other methods, our algorithm is simple to implement and suitable for parallel processing. To achieve the real-time performance, the algorithm is implemented in parallel using GPU (Graphics Processing Unit), and therefore it can be easily integrated into mobile robots’ tasks like navigation and motion control, which need the real-time localization information. Simulations and experiments were conducted to validate the good convergence and longtime robustness performances of the proposed real-time localization algorithm. / With the developed vision based localization method as a position estimator, a new controller for trajectory tracking of the non-holonomic wheeled robot is proposed without direct position measurement. The nonholonomic motion constraint of mobile robots is fully taken into account, compared to most of existing visual sevo controllers for mobile robots. It is proved by Lyapunov theory that the proposed adaptive visual servo controller for the wheeled robot gives rise to asymptotic tracking of a desired trajectory and convergence of the position estimation to the actual position. Experiments on a wheeled robot are conducted to validate the effectiveness and robust performance of the proposed controller. / Adopting the similar idea, the new vision based localization method is once again embedded into a trajectory tracking controller for the underactuated water surface robot. It is proved once again by Lyapunov theory that the proposed adaptive visual servo controller for the underactuated water surface robot gives rise to asymptotic tracking of a desired trajectory and convergence of the position estimation to the actual position. Experiments are conducted on an underactuated water surface robot to validate the effectiveness and robust performance of the proposed controller. / The contribution of this thesis can be summarized as follows: firstly, a novel localization algorithm based on the fusion of the monocular vision and AHRS/odometry sensors is proposed. Secondly, with the former localization method embedded as a position estimator, a new controller for visually servoed trajectory tracking of the nonholonomic wheeled robot is developed. Finally, by adopting the similar strategy, this thesis proposes a new controller for visually servoed trajectory tracking of the underactuated water surface robot without direct position measurement. / 定位是移動機器人中最困難和花費最高的問題之一。由於其低成本和在無GPS（全球定位系統）環境中的有效性，視覺和里程計/ AHRS（姿態航向參考系統，三軸陀螺儀，加速度計和磁力計）傳感器融合是近年來流行的機器人定位策略。這篇論文提出了一種新的自適應估計算法，融合單目視覺和里程計/ AHRS 傳感器，並利用透視投影的特性來估計機器人位置。利用這種新方法，機器人可以實時地在無GPS 和無地圖的環境中被定位，而且定位結果可從理論上證明收斂到他們的真實值。與其它方法相比，我們的算法很容易實現，並適於並行處理。為了得到實時性能，算法是用GPU（圖形處理單元）來並行實現的，因此它可以很容易地集成到移動機器人需要實時定位信息的任務，如導航和運動控制。仿真和實驗驗證了我們的實時定位算法具有很好的收斂及長時間的魯棒表現。 / 利用上述基於視覺的定位方法作為位置估計器，我們為一階非完整移動機器人的軌跡跟踪提出了一種新的、不直接依賴位置測量的控制器。相比於大多數現有的用於移動機器人的視覺伺服控制器，我們的方法充分考慮了移動機器人的非完整運動約束。我們通過Lyapunov穩定性理論證明了本論文所提出的自適應視覺伺服控制器可以保證一階非完整移動機器人對理想軌跡的跟蹤，並且被估計的機器人位置會漸近收斂到其實際的位置。我們在輪式機器人上進行了相應的實驗，驗證了本論文所提出的控制器的有效性和魯棒性。 / 採用類似的思路，這種基於視覺的定位方法被再次嵌入到二階非完整移動機器人（欠驅動水面機器人）的軌跡跟踪控制器。我們再一次通過Lyapunov穩定性理論證明了本論文所提出的自適應視覺伺服控制器可以保證二階非完整移動機器人對理想軌跡的跟蹤，並且被估計的機器人位置會漸近收斂到其iv實際的位置。我們在欠驅動水面機器人上進行了相應的實驗，驗證了本論文所提出的控制器的有效性和魯棒性。 / 這篇論文的貢獻可以歸納如下：首先，基於單目視覺和AHRS/測距傳感器的融合，我們提出了一種新的定位算法。其次，通過將上述基於視覺的定位方法內嵌為位置估計器，我們為一階非完整移動機器人（輪式機器人）設計了一種新的基於視覺伺服的軌跡跟踪控制器。最後，通過採用類似的避免機器人位置測量的策略，本文為二階非完整移動機器人（欠驅動水面機器人）設計了一種新的基於視覺伺服的軌跡跟踪控制器。 / Wang, Kai. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 93-100). / Abstracts also in Chinese. / Title from PDF title page (viewed on 20, December, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

by Tang Kai Hung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references. / Abstracts in English and Chinese. / Acknowledgements --- p.vi / Abstract --- p.1 / Chapter 1 --- Introduction / Chapter 1.1 --- Motivation --- p.3 / Chapter 1.2 --- Objective --- p.7 / Chapter 1.3 --- Outline --- p.9 / Chapter 2 --- Color Identification / Chapter 2.1 --- Grabbing --- p.11 / Chapter 2.2 --- Digital Image Representation --- p.13 / Chapter 2.3 --- Color Segmentation --- p.15 / Chapter 2.3.1 --- Fuzzy Rule-Based Method --- p.15 / Chapter 2.3.2 --- Fuzzy Clustering Method --- p.20 / Chapter 2.4 --- Conclusion --- p.25 / Chapter 3 --- Shape Recognition / Chapter 3.1 --- Labeling --- p.29 / Chapter 3.1.1 --- Pre-processing --- p.29 / Chapter 3.1.2 --- Connected Components --- p.30 / Chapter 3.2 --- Blob Analysis --- p.33 / Chapter 3.2.1 --- Characteristic Values --- p.33 / Chapter 3.2.2 --- Corner Detection --- p.35 / Chapter 3.3 --- Type Classification --- p.37 / Chapter 3.3.1 --- Standard Blob --- p.37 / Chapter 3.3.2 --- Non-standard Object --- p.39 / Chapter 3.4 --- Flow Chart --- p.39 / Chapter 3.5 --- Point Generation --- p.42 / Chapter 3.5.1 --- Draw the Boundary --- p.42 / Chapter 3.5.2 --- Filling in Color by Lines --- p.48 / Chapter 3.6 --- Conclusion --- p.50 / Chapter 4 --- Drawing / Chapter 4.1 --- Difficulties & Remedies --- p.54 / Chapter 4.1.1 --- Data Transmission Difficulty --- p.54 / Chapter 4.1.2 --- Robot Drawing Plane --- p.56 / Chapter 4.2 --- Coordinates Conversion --- p.59 / Chapter 4.3 --- Quantitative Performance Measure --- p.64 / Chapter 4.4 --- Conclusion --- p.66 / Chapter 5 --- Conclusions & Future Works --- p.69 / Appendix / Bibliography

Lo Wang Tai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 58-63). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Tables of Content --- p.iv / List of Figures --- p.vii / List of Tables --- p.viii / Chapter Chapter1 --- Introduction --- p.1 / Chapter 1.1 --- Internet-based Tele-cooperation --- p.1 / Chapter 1.1.1 --- Cooperative Control of Multiple Robot --- p.1 / Chapter 1.1.2 --- Internet-based Teleoperation --- p.3 / Chapter 1.1.3 --- Time Delay of Internet Communication --- p.4 / Chapter 1.2 --- Related Work --- p.5 / Chapter 1.3 --- Motivation and Contribution --- p.6 / Chapter 1.3.1 --- Motivation --- p.6 / Chapter 1.3.2 --- Contribution --- p.7 / Chapter 1.4 --- Outline of the thesis --- p.8 / Chapter Chapter2 --- The Internet Robotic System --- p.9 / Chapter 2.1 --- System Architecture --- p.9 / Chapter 2.2 --- The Hardware --- p.12 / Chapter 2.2.1 --- Operator System --- p.12 / Chapter 2.2.2 --- Mobile Robot System --- p.13 / Chapter 2.2.3 --- Multi-fingered Robot Hand System --- p.17 / Chapter 2.2.4 --- Visual Tracking System --- p.19 / Chapter 2.3 --- Software Design --- p.21 / Chapter 2.3.1 --- Robot Client and Arm Client --- p.22 / Chapter 2.3.2 --- Robot Server --- p.23 / Chapter 2.3.3 --- Image Server --- p.25 / Chapter 2.3.4 --- Arm Server --- p.75 / Chapter 2.3.5 --- Arm Controller --- p.27 / Chapter 2.3.6 --- Finger Server --- p.27 / Chapter 2.3.7 --- Finger Controller --- p.27 / Chapter 2.3.8 --- Robot Tracker --- p.28 / Chapter 2.3.9 --- Interaction Forwarder --- p.28 / Chapter Chapter3 --- Event-based Control for Force Reflecting Teleoperation --- p.29 / Chapter 3.1 --- Modeling and Control --- p.29 / Chapter 3.1.1 --- Model of Operator System --- p.31 / Chapter 3.1.2 --- Model of Mobile Robot System --- p.33 / Chapter 3.1.3 --- Model of Multi-fingered Hand System --- p.34 / Chapter 3.2 --- Force Feedback Generation --- p.35 / Chapter 3.2.1 --- Obstacle Avoidance --- p.35 / Chapter 3.2.2 --- Singularity Avoidance --- p.38 / Chapter 3.2.3 --- Interaction Rendering --- p.40 / Chapter Chapter4 --- Experiments --- p.42 / Chapter 4.1 --- Experiment1 --- p.42 / Chapter 4.2 --- Experiment2 --- p.47 / Chapter 4.3 --- Experiment3 --- p.52 / Chapter Chapter5 --- Future Wok --- p.54 / Chapter Chapter6 --- Conclusions --- p.56 / Bibliography --- p.58

by Kwok Lai Ho Victor. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 77-82). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background --- p.5 / Chapter 2.1 --- History of Robotics --- p.5 / Chapter 2.2 --- Autonomous Robot Systems --- p.7 / Chapter 2.3 --- 3D Windowing Simulators --- p.8 / Chapter 2.4 --- Robot Simulation in VR --- p.8 / Chapter 3 --- Objective --- p.11 / Chapter 4 --- Articulated Structures --- p.13 / Chapter 4.1 --- Joints and links --- p.13 / Chapter 4.2 --- Degrees of Freedom --- p.16 / Chapter 4.3 --- Denavit-Hartenberg Notation --- p.17 / Chapter 5 --- Virtual Manipulators --- p.20 / Chapter 5.1 --- Arm(N-link) Structure --- p.20 / Chapter 5.2 --- Hand Model --- p.24 / Chapter 6 --- Motion Control Techniques --- p.27 / Chapter 6.1 --- Kinematics --- p.27 / Chapter 6.1.1 --- Forward Kinematics --- p.27 / Chapter 6.1.2 --- Inverse Kinematics --- p.29 / Chapter 6.1.3 --- Solving Kinematics Problem --- p.29 / Chapter 6.1.4 --- Redundancy --- p.31 / Chapter 6.1.5 --- Singularities --- p.32 / Chapter 6.2 --- Dynamics --- p.33 / Chapter 6.2.1 --- Forward Dynamics --- p.34 / Chapter 6.2.2 --- Inverse Dynamics --- p.35 / Chapter 6.3 --- Combination of Two Control Modes --- p.35 / Chapter 6.4 --- Constraints and Optimization --- p.36 / Chapter 7 --- Physical Feedback Systems --- p.38 / Chapter 7.1 --- Touch Feedback --- p.39 / Chapter 7.2 --- Force Feedback --- p.41 / Chapter 7.3 --- Force/Touch Feedback Systems --- p.42 / Chapter 8 --- Virtual Object Manipulation --- p.43 / Chapter 8.1 --- Previous Work --- p.44 / Chapter 8.2 --- Physics-based Virtual-hand Grasping --- p.45 / Chapter 8.3 --- Visual Correction --- p.43 / Chapter 8.3.1 --- Joint Correction --- p.50 / Chapter 8.3.2 --- Odd Finger Configurations --- p.51 / Chapter 8.4 --- Active Grasping --- p.52 / Chapter 8.5 --- Collision Detection of Complex Objects --- p.54 / Chapter 9 --- Experiments --- p.57 / Chapter 9.1 --- System Architecture --- p.57 / Chapter 9.1.1 --- Tracking System --- p.53 / Chapter 9.1.2 --- Glove System --- p.59 / Chapter 9.1.3 --- Host Computer --- p.60 / Chapter 9.2 --- Experimental Results --- p.60 / Chapter 9.2.1 --- General application --- p.61 / Chapter 9.2.2 --- Relationship between frictional coefficient and mass of the object --- p.61 / Chapter 10 --- Conclusions --- p.67 / Chapter 10.1 --- Summary --- p.67 / Chapter 10.2 --- Contributions --- p.69 / Chapter 10.3 --- Future Work --- p.69 / Chapter A --- Description files --- p.71 / Chapter A.1 --- Scene Description --- p.71 / Chapter A.2 --- Hand Description --- p.73 / Bibliography --- p.77

Zhang Yu-nong. / "November 2002." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (p. 161-176). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

As a result, this dissertation proposes a novel type of tree climbing robot, named Treebot, which has high maneuverability on trees. The design of Treebot was inspired by arboreal animals such as squirrels and inchworms. The applied extendable continuum maneuvering mechanism has large workspace and high degrees of freedom. It allows Treebot to perform various actions, such as moving between trunk and branches. Treebot is able to grip the surface of trees tightly with a wide range of gripping curvature. It enables Treebot to grip from a big tree trunk to small branches. The special gripping mechanism allows zero energy consumption in static gripping. Although Treebot has high maneuverability, it is compact, lightweight, and only five actuators are used in total. By installing proper equipments, Treebot can assist workers to perform forestry tasks such as inspection and maintenance. It can also be used as a mobile surveillance system to observe behaviors of both ground and arboreal animals. / Climbing robots have become a hot research topic in recent decades. Most research in this area focuses on climbing manmade structures, such as vertical walls, glass windows, and structural frames. Little research has been conducted specifically on climbing natural structures such as trees. The nature of trees and manmade structures is very different. For example, trees have an irregular shape and their surface is not smooth. Some types of trees have soft bark that peels off easily. Hence, most of the climbing methods for manmade structures are not applicable to tree climbing. / In addition to presenting the mechanical design of Treebot, this dissertation also proposes several autonomous tree climbing algorithms. Making a robot climb a tree autonomously is a challenging task, as trees are complex and irregular in shape. However, a certain level of autonomous climbing ability is needed to simplify the operational use of Treebot. The proposed works include autonomous climbing on unknown environment and global path planning on known environment. / Preventing trees from failing is important to protect human life and property in urban areas. Most trees in urban areas require regular maintenance. To reach the upper parts of a tree to perform such maintenance, workers need to climb the tree. However, tree climbing is dangerous, the development of a tree climbing robot is important to assist or replace humans works. / Several robots have been designed to climb trees such as WOODY and RiSE. However, these robots are limited to climbing straight tree trunks, and cannot climb trees that are curved or have branches. As branches and curvature are present in almost all trees, the application of these robots is strongly restricted. / Lam, Tin Lun. / Adviser: Yangsheng Xu. / Source: Dissertation Abstracts International, Volume: 73-03, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 163-172). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

by Law Kwok Ho Cedric. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 106-112). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Related work --- p.4 / Chapter 1.3 --- Thesis overview --- p.5 / Chapter 2 --- Single wheel robot: Gyrover --- p.9 / Chapter 2.1 --- Background --- p.9 / Chapter 2.2 --- Robot concept --- p.11 / Chapter 2.3 --- System description --- p.14 / Chapter 2.4 --- Flywheel characteristics --- p.16 / Chapter 2.5 --- Control patterns --- p.20 / Chapter 3 --- Learning Control --- p.22 / Chapter 3.1 --- Motivation --- p.22 / Chapter 3.2 --- Cascade Neural Network with Kalman filtering --- p.24 / Chapter 3.3 --- Learning architecture --- p.27 / Chapter 3.4 --- Input space --- p.29 / Chapter 3.5 --- Model evaluation --- p.30 / Chapter 3.6 --- Training procedures --- p.35 / Chapter 4 --- Control Architecture --- p.38 / Chapter 4.1 --- Behavior-based approach --- p.38 / Chapter 4.1.1 --- Concept and applications --- p.39 / Chapter 4.1.2 --- Levels of competence --- p.44 / Chapter 4.2 --- Behavior-based control of Gyrover: architecture --- p.45 / Chapter 4.3 --- Behavior-based control of Gyrover: case studies --- p.50 / Chapter 4.3.1 --- Vertical balancing --- p.51 / Chapter 4.3.2 --- Tiltup motion --- p.52 / Chapter 4.4 --- Discussions --- p.53 / Chapter 5 --- Implement ation of Learning Control --- p.57 / Chapter 5.1 --- Validation --- p.57 / Chapter 5.1.1 --- Vertical balancing --- p.58 / Chapter 5.1.2 --- Tilt-up motion --- p.62 / Chapter 5.1.3 --- Discussions --- p.62 / Chapter 5.2 --- Implementation --- p.65 / Chapter 5.2.1 --- Vertical balanced motion --- p.65 / Chapter 5.2.2 --- Tilt-up motion --- p.68 / Chapter 5.3 --- Combined motion --- p.70 / Chapter 5.4 --- Discussions --- p.72 / Chapter 6 --- Shared Control --- p.74 / Chapter 6.1 --- Concept --- p.74 / Chapter 6.2 --- Schemes --- p.78 / Chapter 6.2.1 --- Switch mode --- p.79 / Chapter 6.2.2 --- Distributed mode --- p.79 / Chapter 6.2.3 --- Combined mode --- p.80 / Chapter 6.3 --- Shared control of Gyrover --- p.81 / Chapter 6.4 --- How to share --- p.83 / Chapter 6.5 --- Experimental study --- p.88 / Chapter 6.5.1 --- Heading control --- p.89 / Chapter 6.5.2 --- Straight path --- p.90 / Chapter 6.5.3 --- Circular path --- p.91 / Chapter 6.5.4 --- Point-to-point navigation --- p.94 / Chapter 6.6 --- Discussions --- p.95 / Chapter 7 --- Conclusion --- p.103 / Chapter 7.1 --- Contributions --- p.103 / Chapter 7.2 --- Future work --- p.104

Tong, Fung Ling. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 94-96). / Abstracts in English and Chinese. / Abstract --- p.i / 摘要 --- p.iii / Acknowledgement --- p.iii / Table of Contents --- p.iv / List of Figures --- p.vii / List of Tables --- p.x / Chapter Chapter 1 - --- Introduction --- p.1 / Chapter Chapter 2 - --- State of the art in Vision-based Localization --- p.6 / Chapter 2.1 --- Extended Kalman Filter-based Localization --- p.6 / Chapter 2.1.1 --- Overview of the EKF algorithm --- p.6 / Chapter 2.1.2 --- Process of the EKF-based localization algorithm --- p.8 / Chapter 2.1.3 --- Recent EKF-based vision-based localization algorithms --- p.10 / Chapter 2.1.4 --- Advantages of the EKF-based localization algorithms --- p.11 / Chapter 2.1.5 --- Disadvantages of the EKF-based localization algorithm --- p.11 / Chapter 2.2 --- Monte Carlo Localization --- p.12 / Chapter 2.2.1 --- Overview of MCL --- p.12 / Chapter 2.2.2 --- Recent MCL-based localization algorithms --- p.14 / Chapter 2.2.3 --- Advantages of the MCL-based algorithm --- p.15 / Chapter 2.2.4 --- Disadvantages of the MCL-based algorithm --- p.16 / Chapter 2.3 --- Summary --- p.16 / Chapter Chapter 3 - --- Vision-based Localization as an Optimization Problem --- p.18 / Chapter 3.1 --- "Relationship between the World, Camera and Robot Body Coordinate System" --- p.18 / Chapter 3.2 --- Formulation of the Vision-based Localization as an Optimization Problem --- p.21 / Chapter 3.3 --- Summary --- p.26 / Chapter Chapter 4 - --- Existing Search Algorithms --- p.27 / Chapter 4.1 --- Overview of the Existing Search Algorithms --- p.27 / Chapter 4.2 --- Search Algorithm for the Proposed Objective Function --- p.28 / Chapter 4.3 --- Summary --- p.30 / Chapter Chapter 5 - --- Proposed Vision-based Localization using Genetic Algorithm --- p.32 / Chapter 5.1 --- Mechanism of Genetic Algorithm --- p.32 / Chapter 5.2 --- Formation of Chromosome --- p.35 / Chapter 5.3 --- Fitness Function --- p.39 / Chapter 5.4 --- Mutation and Crossover --- p.40 / Chapter 5.5 --- Selection and Stopping Criteria --- p.42 / Chapter 5.6 --- Adaptive Search Space --- p.44 / Chapter 5.7 --- Overall Flow of the Proposed Algorithm --- p.46 / Chapter 5.8 --- Summary --- p.47 / Chapter Chapter 6 - --- Experimental Results --- p.48 / Chapter 6.1 --- Test Robot --- p.48 / Chapter 6.2 --- Simulator --- p.49 / Chapter 6.2.1 --- Camera states simulation --- p.49 / Chapter 6.2.2 --- Oscillated walking motion simulation --- p.50 / Chapter 6.2.3 --- Input images simulation --- p.50 / Chapter 6.3 --- Computer for simulations --- p.51 / Chapter 6.4 --- Position and Orientation errors --- p.51 / Chapter 6.5 --- Experiment 1 一 Feature points with quantized noise --- p.53 / Chapter 6.5.1 --- Setup --- p.53 / Chapter 6.5.2 --- Results --- p.56 / Chapter 6.6 --- Experiment 2 一 Feature points added with Gaussian noise --- p.62 / Chapter 6.6.1 --- Setup --- p.62 / Chapter 6.6.2 --- Results --- p.62 / Chapter 6.7 --- Experiment 3 一 Noise reduction performance of the adaptive search space strategy --- p.77 / Chapter 6.7.1 --- Setup --- p.77 / Chapter 6.7.2 --- Results --- p.79 / Chapter 6.8 --- Experiment 4 一 Comparison with benchmark algorithms --- p.83 / Chapter 6.8.1 --- Setup --- p.83 / Chapter 6.8.2 --- Results --- p.85 / Chapter 6.9 --- Discussions --- p.88 / Chapter 6.10 --- Summary --- p.90 / Chapter Chapter 7- --- Conclusion --- p.91 / References --- p.94