多載具編隊運動之即時避障策略設計

Abstract

本論文研究主旨在整合硬體與路徑規劃的演算法，設計多載具編隊的即時避障策略並實現之。 我們採用擬剛體編隊法設計多載具的運動隊形，係將擬剛體的形變理論應用在編隊的設計上，使多載具的隊伍形狀由一組空間齊性形變張量來決定，容許隊形拉伸、旋轉、剪變，此隊形比起剛體隊形更能適應較複雜的環境。編隊設計為先利用快速探索隨機樹(RRT)，配合路線平滑的技巧，建構出隊形的中心路徑。接著設計虛擬位能函數來得到擬剛體的形變張量，可得各載具之規畫路徑。 系統首先由Kinect初步偵測環境並於主控電腦規劃路徑，並於載具運動中加入即時避障功能；針對即時避障問題，首先由單載具出發討論避障策略，隨後討論多載具即時避障問題，本論文利用模糊邏輯理論和多載具之協同機制，即時調整齊性形變張量參數，使得編隊運動能避開短距離障礙物，並在過程中仍能維持擬剛體隊形。經實驗證明，本文所提出的策略確實可行。

The purpose of this thesis is to integrate the hardware and the path-planning algorithm, and then to design a real-time obstacle-avoidance strategy for a multi-vehicle system, which is realized with a system of three vehicles. The pseudo-rigid formation design algorithm was adopted to design the formation of the multi-vehicle system. The algorithm applies the idea of pseudo-rigid body theory to the formation design, which is determined by a homogenous deformation tensor such that stretch, rotation, and shear are allowed. Comparing to rigid body formation design, pseudo-rigid formation has a better adaptability to environments of higher complexity. In this method, the Rapidly-Exploring Random Tree (RRT) method was first used along with the techniques of route adjustment to obtain the route of the formation center. The deformation matrix is then found by the method of virtual potential function, from which the route of each vehicle is computed. We utilize Microsoft’s Kinect to initially detect environmental objects and execute path-planning design first, and then the function of real-time obstacle-avoidance during the motion of vehicles is implemented. With regard to the problem of obstacle-avoidance, we discuss the strategy for the single vehicle first, which is followed by the discussion for the case of a three-vehicle system. Fuzzy theory and the coordinated control algorithm were used for the multi-vehicle system to adjust the parameter of the deformation matrix in real-time. The vehicles were driven to avoid the obstacles in short distance, while the pseudo-rigid formation is kept during the process. Experimental results show that the strategy proposed in this thesis for a multi-vehicle system is feasible.