面向空中—水面協(xié)作的自主起降系統(tǒng)設(shè)計(jì)及控制
[Abstract]:In recent years, the field mobile robot has made great progress. The autonomous control system of unmanned mobile platform represented by unmanned aerial vehicle, unmanned vessel and unmanned vehicle is becoming more and more mature, and the behavior planning of mobile robot is becoming more and more perfect. The main problem in mobile robot research is the lack of environmental perception. Small UAVs have been widely used in many fields because of their high speed, easy to carry and wide angle of view. But its shortcomings are also very prominent, such as poor endurance, the general multi-rotor UAV can only fly for about 20 minutes, the environmental perception accuracy is low, unable to obtain local accurate environmental information. Because of its heavy load and long duration, unmanned ship can install multiple sensors to obtain accurate local information, but it is difficult to obtain global environmental information because of its low sensor installation position. Therefore, we bring forward the concept of airborne and surface subrobot system, which is expected to combine the wide-area environmental perception and maneuverability of UAV with the local environment fine perception and long-lasting capability of surface robot. Improve the perception and autonomous behavior performance of the whole system in complex environment. Since unmanned aerial vehicles (UAVs) need to take off and land independently on unmanned ships many times, the autonomous take-off and landing system is an indispensable and crucial part in the sub-mother robot system. Only on the basis that autonomous take-off and landing can be successfully completed, can air surface cooperation become possible with subsequent environmental awareness. Aiming at the problems of UAV's autonomous take-off and landing, such as UAV positioning, communication between UAV and UAV, UAV tracking of UAV, autonomous take-off and landing control strategy, a set of solution is designed in this paper. The thesis mainly includes the following four parts: (1) firstly, differential GPS is used to locate the UAV, and the gyroscopes and accelerometers are fused by Kalman filter. Electronic compass and other sensor information to improve UAV positioning accuracy and frequency. This paper introduces the method of attitude calculation using quaternion pair UAV and the PID controller to realize position control. (2) the communication protocol between UAV and UAV is completed, including the control instruction of UAV. The position and attitude information of UAV and unmanned vessel are exchanged. (3) A set of auxiliary mechanism for take-off and landing is designed. The mechanism is composed of two harpoons and is mounted on both sides of the landing gear. It adopts passive anchoring, is simple and reliable, and can be used repeatedly. It can meet the need of UAV to take off and land on unmanned ship many times. (4) the tracking control algorithm of UAV to unmanned ship is designed at the same time, and part of the cooperative function is completed.
【學(xué)位授予單位】:沈陽(yáng)理工大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:V249;TP242
【相似文獻(xiàn)】
相關(guān)博士學(xué)位論文 前4條
1 劉篤晉;面向植被識(shí)別的無人機(jī)圖像處理關(guān)鍵技術(shù)研究[D];成都理工大學(xué);2016年
2 賈樹蔥;智能交通網(wǎng)絡(luò)中資源競(jìng)爭(zhēng)與合作機(jī)制研究[D];北京郵電大學(xué);2017年
3 穆悅;戈壁表面多尺度礫石特征參數(shù)估算及其空間分布規(guī)律研究[D];中國(guó)林業(yè)科學(xué)研究院;2017年
4 袁建清;基于多尺度遙感的寒地水稻稻瘟病信息提取與識(shí)別研究[D];東北農(nóng)業(yè)大學(xué);2017年
相關(guān)碩士學(xué)位論文 前10條
1 張紀(jì)敏;面向空中—水面協(xié)作的自主起降系統(tǒng)設(shè)計(jì)及控制[D];沈陽(yáng)理工大學(xué);2017年
2 李洪向;基于無人車和無人機(jī)協(xié)作的動(dòng)態(tài)降落研究[D];哈爾濱工業(yè)大學(xué);2017年
3 麥貴林;電力巡線無人機(jī)的測(cè)向與定位技術(shù)研究[D];哈爾濱工業(yè)大學(xué);2017年
4 雷雨默;多旋翼無人機(jī)堆狀體航空攝影測(cè)量[D];西安科技大學(xué);2017年
5 魏江鵬;小型多功能無人機(jī)設(shè)計(jì)優(yōu)化與控制[D];長(zhǎng)安大學(xué);2017年
6 郭倩倩;無人機(jī)天線自動(dòng)跟蹤系統(tǒng)的設(shè)計(jì)[D];杭州電子科技大學(xué);2017年
7 劉見禮;基于無人機(jī)立體影像數(shù)據(jù)的森林結(jié)構(gòu)參數(shù)調(diào)查研究[D];中國(guó)科學(xué)院大學(xué)(中國(guó)科學(xué)院遙感與數(shù)字地球研究所);2017年
8 王斌;八旋翼電動(dòng)植保無人機(jī)的研制與試驗(yàn)分析[D];吉林農(nóng)業(yè)大學(xué);2017年
9 溫爾雅;無人機(jī)圖像處理關(guān)鍵技術(shù)的研究與實(shí)現(xiàn)[D];電子科技大學(xué);2017年
10 莫德強(qiáng);基于無人機(jī)平臺(tái)的道路車輛違章超速行為檢測(cè)算法研究[D];哈爾濱工業(yè)大學(xué);2017年
,本文編號(hào):2341966
本文鏈接:http://www.sikaile.net/kejilunwen/zidonghuakongzhilunwen/2341966.html