本文選題：旋翼無人機(jī) + 計(jì)算機(jī)視覺��； 參考：《上海交通大學(xué)》2015年碩士論文

【摘要】：近年來,旋翼無人機(jī)因其優(yōu)秀的機(jī)動(dòng)性能在各個(gè)領(lǐng)域的應(yīng)用都受到了高度重視。為了使操控更便利、控制更精準(zhǔn),根據(jù)視覺信息對(duì)無人機(jī)進(jìn)行位置姿態(tài)控制一直是研究熱點(diǎn)。自主返航也是無人機(jī)的一個(gè)重要功能,目前多旋翼無人機(jī)產(chǎn)品的飛控系統(tǒng)大多提供基于衛(wèi)星導(dǎo)航信號(hào)的一鍵返航功能,但是在某些復(fù)雜環(huán)境中衛(wèi)星導(dǎo)航信號(hào)并不可靠。本文的研究目的就是基于視覺信息對(duì)旋翼無人機(jī)的位置姿態(tài)進(jìn)行精確控制,并實(shí)現(xiàn)自主返航功能。首先,本文根據(jù)無人機(jī)底部垂直向下的攝像頭圖像的光流與慣導(dǎo)器件融合得到的無人機(jī)估算速度,引入速度控制器以改善無人機(jī)位姿控制的效果。四旋翼機(jī)飛行實(shí)驗(yàn)證明提出的控制算法能更好地實(shí)現(xiàn)基于地標(biāo)物的定點(diǎn)懸停、自主循跡,同時(shí)對(duì)速度信息進(jìn)行積分可以得到比較準(zhǔn)確的無人機(jī)的相對(duì)位移。在此基礎(chǔ)之上,本文利用無人機(jī)前部攝像頭實(shí)現(xiàn)自主返航功能。根據(jù)計(jì)算機(jī)視覺多視角幾何理論,對(duì)相機(jī)當(dāng)前圖像與關(guān)鍵幀進(jìn)行匹配可以解算兩個(gè)視角的三維變換關(guān)系,從而控制無人機(jī)逼近關(guān)鍵幀位置并懸停。本文提出的魯棒的自主返航技術(shù)方案結(jié)合了估算速度導(dǎo)航與圖像匹配懸停:在去程中,無人機(jī)每隔一定距離記錄一次位移信息、偏航角與圖像關(guān)鍵幀;在回程時(shí),無人機(jī)先根據(jù)位移信息到達(dá)關(guān)鍵幀附近,然后通過圖像匹配糾正誤差,對(duì)下一幀重復(fù)這兩ki直到回到起點(diǎn)。仿真實(shí)驗(yàn)證明本文所述方法能實(shí)現(xiàn)自主返航功能,且可以應(yīng)對(duì)復(fù)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(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：V279;V249

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相關(guān)期刊論文 前2條

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本文編號(hào)：2020746