本論文探討由三台四輪全向移動機器人所構成的多機器人系統(Multi-Robot System, MRS)之編隊控制(Formation Control)，並以系統晶片(System on Programmable Chip, SoPC)實現其設計。首先，針對單台機器人進行其運動學與動力學分析，並設計出機器人的動力學控制器。再分別導入徑向基函數神經網路(Radial Basis Function Neural Network, RBFNN)與多層感知機(Multilayer Perceptron, MLP)模型，使得控制器可以根據控制表現自我修改其控制參數，成為自適應控制器。針對RBFNN及MLP模型，則導入數種搜索式演算法如基因演算法(Genetic Algorithm, GA)、螢火蟲演算法(Firefly Algorithm, FA)及其變種等，來尋找上述人工神經網路模型的最佳參數，使得控制系統得以最佳化，並比較不同演算法的搜索表現。完成單台機器人的設計後，藉由座標轉換與幾何學設計出多機器人系統的編隊控制演算法，其可讓多機器人在進行軌跡追蹤的同時，保持其編隊隊形。至於機器人硬體開發採用Altera公司所生產的DE1-SoC嵌入式系統開發板，並將設計完成的系統以SoPC的技術實現。並使用TCP/IP通訊協定與Socket技術建立機器人彼此間的連線。最後藉由分析系統在MATLAB軟體中的模擬結果，與實際實驗中的結果，驗證本研究的設計正確性及其優點。

This thesis presents the formation control method of the multi-robot system, constructed by three four-wheeled omnidirectional mobile robots, and its implementation by using the system on programmable chip (SoPC). First, we analyze the kinematics and dynamics of a single robot, and then design the controller. Models of Radial Basis Function Neural Network (RBFNN) and Multilayer Perceptron (MLP) are also incorporated with the controller to make it become an adaptive controller able to adjust its control parameters with controlling behavior. Several heuristic algorithms like Genetic Algorithm (GA), Firefly Algorithm (FA), and their variation are introduced to achieve the optimization of parameters of RBFNN and MLP models. We also compare the search performance of different algorithms. After finishing the design of a single robot, we then design the formation control algorithm of the multi-robot system by using transformation of coordinates and geometry. Such design can enable the robots to track their desired trajectory while maintaining their formation shape at the same time. The development of robot’s hardware is based on DE1-SoC development board produced by Altera Corporation to fulfill the design of the system with SoPC technology. TCP/IP protocol and Socket technique are also used to construct connection between robots. Finally, simulation results by using MATLAB and physical experimental results show the correctness and advantages by using proposed methods.

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