本文選題：旋翼無人機 + 計算機視覺��； 參考：《上海交通大學》2015年碩士論文

【摘要】：近年來,旋翼無人機因其優(yōu)秀的機動性能在各個領域的應用都受到了高度重視。為了使操控更便利、控制更精準,根據視覺信息對無人機進行位置姿態(tài)控制一直是研究熱點。自主返航也是無人機的一個重要功能,目前多旋翼無人機產品的飛控系統(tǒng)大多提供基于衛(wèi)星導航信號的一鍵返航功能,但是在某些復雜環(huán)境中衛(wèi)星導航信號并不可靠。本文的研究目的就是基于視覺信息對旋翼無人機的位置姿態(tài)進行精確控制,并實現自主返航功能。首先,本文根據無人機底部垂直向下的攝像頭圖像的光流與慣導器件融合得到的無人機估算速度,引入速度控制器以改善無人機位姿控制的效果。四旋翼機飛行實驗證明提出的控制算法能更好地實現基于地標物的定點懸停、自主循跡,同時對速度信息進行積分可以得到比較準確的無人機的相對位移。在此基礎之上,本文利用無人機前部攝像頭實現自主返航功能。根據計算機視覺多視角幾何理論,對相機當前圖像與關鍵幀進行匹配可以解算兩個視角的三維變換關系,從而控制無人機逼近關鍵幀位置并懸停。本文提出的魯棒的自主返航技術方案結合了估算速度導航與圖像匹配懸停:在去程中,無人機每隔一定距離記錄一次位移信息、偏航角與圖像關鍵幀;在回程時,無人機先根據位移信息到達關鍵幀附近,然后通過圖像匹配糾正誤差,對下一幀重復這兩ki直到回到起點。仿真實驗證明本文所述方法能實現自主返航功能,且可以應對復雜的路徑與偏航角改變的情況。
[Abstract]:In recent years, the rotor UAV has been attached great importance for its excellent maneuverability. In order to make the control more convenient and accurate, the position and attitude control of UAV based on visual information has been a hot topic. Autonomous return is also an important function of UAV. At present, most of the flight control systems of multi-rotor UAV products provide one-click return function based on satellite navigation signal, but the satellite navigation signal is not reliable in some complex environments. The purpose of this paper is to accurately control the position and attitude of the rotoring UAV based on visual information, and to realize the function of autonomous return. Firstly, this paper introduces a speed controller to improve the performance of UAV position and attitude control based on the fusion of optical flow and inertial navigation devices of the camera image at the bottom of the UAV. The flight experiments of the four-rotorcraft show that the proposed control algorithm can better achieve the land-based hovering of fixed points, independent tracking, and the integration of velocity information can obtain a more accurate relative displacement of UAV. On this basis, this paper uses the UAV front camera to achieve autonomous return function. According to the theory of multi-view geometry of computer vision, the 3D transformation relationship between the two angles of view can be solved by matching the current camera image with the key frame, thus controlling the UAV to approach the position of the key frame and hover. The robust autonomous return scheme proposed in this paper combines the estimation of velocity navigation with image matching hovering: during the journey, the UAV records displacement information, yaw angle and image key frame at a certain distance. The UAV first arrives near the key frame according to the displacement information, then corrects the error by image matching, repeats the two Ki to the next frame until it returns to the starting point. The simulation results show that the proposed method can realize the autonomous return function and can deal with the complex path and yaw angle changes.
【學位授予單位】：上海交通大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：V279;V249

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本文編號：2020746