工學院: 應用力學研究所指導教授: 王立昇黃哲文Huang, Jer-WenJer-WenHuang2017-03-062018-06-292017-03-062018-06-292016http://ntur.lib.ntu.edu.tw//handle/246246/277323本文主旨為建立用於擬剛體編隊控制之載具定位與姿態識別系統，裝設一台位於高處的攝影機，結合影像校正與定位演算法，提供一個全域座標系統給擬剛體隊形系統進行環境的辨識與各載具的位置與姿態掌握，將原本獨立的各載具編至成擬剛體隊形後，再配合擬剛體為隊形搭配路徑規劃演算法，實際整合軟硬體並進行實驗。 我們以擬剛體編隊法設計多載具的運動隊形，並將擬剛體的形變理論應用在編隊設計上，使多載具隊伍形狀由一組空間齊性形變張量來決定。擬剛體隊形容許旋轉、拉伸、剪變。而此具規則性的隊形比起剛體隊形更能適應於複雜環境。在路徑規劃部份以快速探索隨機樹(RRT)及路徑平滑技巧，規劃隊形的中心路徑。接著設計內部及外部虛擬位能函數來得到擬剛體的形變張量，求得各載具之參考路徑。 於實驗部份，我們首先以M3006V網路攝影機偵測各載具的座標位置與其姿態，接著計算出個別載具與其所設定的擬剛體隊形位置距離與期望的姿態夾角，再回傳給主控電腦進行編隊初始化的任務。 完成編隊初始化後，我們首先以Kinect初步偵測環境並將資訊傳送到主控電腦做路徑規劃，於隊伍運動中以多載具協同機制，控制載具間的運動關係；位於高處的攝影機提供了對擬剛體編隊運行進行監控以及後方障礙物的真實情況，提高了隊伍運行靈活度。The purpose of this thesis is to develop a global vision system for the pseudo-rigid formation control of a multi-vehicle system. An IP camera installed on the roof(three-meter high) was used to provide the position coordinates and attitude angles of the vehicles. With camera calibration and vision positioning algorithm, we use this vision system to gather prior information for each vehicle and conduct the experiment by integrating hardware and software. The algorithm we applied to design the formation of vehicles is based on the pseudo-rigid body theory, which is determined by a homogenous deformation tensor such that rotation, stretch, and shear are allowed. This formation has a better adaptability to complex environment comparing to the rigid-body formation. The Rapidly-Exploring Random Tree (RRT) method along with the techniques of route adjustment were adopted to obtain the path of formation center. The deformation matrix is then found by using the method of virtual potential function, from which the route of each vehicle is computed. In the experiments, we used M3006V IP camera to detect the locations and attitude angles of each vehicle, desired distances and angles that the vehicles need to move to form a pseudo-rigid formation are calculated. These information is then transfer to the base station to initialize the pseudo-rigid formation. After the initialization of the pseudo-rigid formation, Microsoft’s Kinect sensor was used to detect the environment. The path-planning algorithm on the leader computer was then invoked to obtain the path of the formation center. The pseudo-rigid formation design algorithm based on the virtual potential theory was conducted to yield the desired path of each vehicle. The camera can monitor the real route and real environment behind obstacles, so that the adaptivity of pseudo-rigid formation control can be improved.3196799 bytesapplication/pdf論文公開時間: 2021/8/26論文使用權限: 同意有償授權(權利金給回饋學校)擬剛體編隊避障路徑規劃模糊控制Pseudo-Rigid BodyFormationObstacle-AvoidancePath-PlanningFuzzy controlthesis10.6342/NTU201603230http://ntur.lib.ntu.edu.tw/bitstream/246246/277323/1/ntu-105-R03543054-1.pdf