基于仿生鱼群优化方法的机器人队形控制

本文利用人工鱼群优化（AFSO）方法研究了多机器人的队形控制问题。机器人编队可视为寻迹问题，而编队寻迹是不断减小机器人与其期望编队位置之间的平移和角度误差的优化过程。每一个机器人的控制指令可看做是人工鱼群，通过一系列的控制实现期望队形。队形控制策略中包含机器人间的冲突规避行为。本文利用Matlab中的多机器人仿真器MRsim工具进行了仿真，结果表明本文提出的方法具有很高的有效性和效率，适用于各种形式的队形，可以被广泛应用在没有精确系统模型的无线传感器网络中。

Artificial fish swarm optimization-based formation control of nonholonomic mobile robots

The problem of formation control of nonholonomic mobile robots is investigated using the artificial fish swarm optimization (AFSO).The formation of the robots is treated as a tracking problem, The formation tracking is set as an optimization problem, minimizing the translational and angular errors between the robot and its desired formation position. The control commands for each robot are treated as artificial fishes in a swarm and a sequence of controls is derived to achieve the desired formation. The behavior of inter-robots collision avoidance is incorporated in the formation control strategies. This paper conducts a simulation using Matlab multi-robots simulator MR Sim , the result illustrate the effectiveness and the robustness of the proposed method for various kind of formations, this method can be used widely for mobile sensors networks where no precise system model is provided.