相對於在地面上行走的機器人, 自動無人飛機擁有高自由度及靈活操控性。在對人類有危險的環境中，無人飛機更特別可以全自動或供操作員安全地遙距控制來執行危險工作。但無線連結不能確保安全及穩定，所以基於安全性考慮自動無人機上必需擁有自主運算能力以用於自動定位，返航及避障。 / 可是制作全自動無人機有很多的限制，如小型無人飛機上只能使用較小型馬達，載重十分少，故能被作為主要的計算機也不能使用強大的圖像處理器(GPU)，所以只能使用運算能力較低的一般處理器(CPU)。此外，傳統的圖像處理定位方法也只能在強大硬件下實時運行，這種種的限制加起來使得小型無人飛機的自動定位成為難題。 / 一般現在的無人機，例如作為航空拍攝的，都是使用簡單而小型的全球定位系統感測器，所需要的運算器硬件要求也不高。但是這些無人飛機卻不能被用於室內或靠近建築物的地方，因為衛星定位信號會被多重反射甚至是阻隔開來。此外，全球定位系統普不能給予無人機有關機體附近環境的訊息，例如視覺特徵及三維結構等。所以無人機並沒有能力避開環境中的障礙物或甚至危害人身安全。 / 我們設計了飛行控制器，內含恣態感測組件，光流傳感器及高度計等元件作控制及感測。我們也提出了一個全自動的校準方法用於低成本的恣態感測器，當中並不需要任何人為的操作或昂貴和精準的的校準儀器。 / 除了恣態感測組件用於機體動作測量外，環境資訊都是對自動飛行有很大用的。我們所建構的無人飛機平台上使用了多種不同的運算組件及視覺定位算法，目的在於提拱一個有效,快速且能於飛機上裝置的電腦實時運算的定位系統。 / 從本論文所展示的結果中可得悉我們在無人機的及展，包括如何把低成本的恣態感測器校正的方法以增加準確性及從環境視覺特徵及三維結構幫助計算無人機自身位置的定位方法。我們希望本研究論文能對下一世代的自動無人機發展有幫助。 / Unmanned Aerial Vehicles (UAVs) process great maneuverability over ground vehicles, legged and tracked robots. UAVs can do more dangerous tasks where human can safely tele-operate from far away. However stable communication channels may not be guaranteed and therefore autonomous onboard processing for safety-concerned functions such as localization, homing or obstacles avoidance are essential. / UAVs have more limitations than others, typically the payload weight is significantly reduced compared to ground vehicles with powerful motors. Other limitations such as limited computing power for light-weight computer modules being put on-board lend the difficulty to the localization and control of the agile UAVs using traditional computationally exhausting Visual SLAM approaches. / Although the traditional simple GPS-Inertial approaches are beautiful that the hardware requirement is not so demanding, they cannot be applied in indoor or near indoor environments due to signal jamming and multiple-reflection. Additionally, GPS cannot provide any information about the environment arround the UAV so it raises risk for the UAV to danger such as obstacles collision which may cause serious injury to human. / To implement an autonomous aerial vehicle we built our flight-controller with a low-cost inertial measurement unit (IMU) and optical ow sensor and altimeter for motor control and sensing. The low-cost IMU suffers from bad measurement bias and drifts. We proposed a fully autonomous calibration method where no human intervention nor precise calibration equipment is needed. / Besides the IMU which can only provide body motion sensing, the perception about the environment is required for autonomous flying and avoid obstacles. We implemented a visual localization algorithm which runs efficiently in realtime on our light-weight and low-cost computer module. We have built a set of UAV system with an RGB-D Kinect sensor, which fuse different sensor measurements together for the localization. / The results presented in this thesis show a new possiblity to advance current development on Unmanned Aerial Vehicles. From the autonomous calibration method for low-cost IMU to improve accuracy orientation estimation to 3D localization using the perception of the environment features and structures from RGB-D sensor. At the same time we hope that our experience on the hardware building and real-time localization algorithm implementations can help boosting the advancement of the next generation of autonomous aerial vehicles. / Cheuk, Chi Ming. / Thesis M.Phil. Chinese University of Hong Kong 2015. / Includes bibliographical references (leaves 88-96). / Abstracts also in Chinese. / Title from PDF title page (viewed on 05, October, 2016). / Cheuk, Chi Ming. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.