无领导群体编队控制：从全局规范到局部控制律
Leaderless Swarm Formation Control: From Global Specifications to Local Control Laws
摘要：
本文介绍了一种分布式无领导群体编队控制框架，以解决集体驱动一群机器人跟踪时变编队的问题。群的形成是由一个抽象的形状，外接的机器人的位置的凸包的轨迹，是独立的机器人的数量和它们在群中的顺序。对于每个机器人在群中，给定的全球规格的抽象形状参数的轨迹，所提出的框架合成的控制律，引导群跟踪所需的形成使用的信息，在机器人的本地邻居。为了这个目的，我们产生一个合适的本地参考轨迹，机器人控制器通过解决输入输出线性化问题的跟踪。在这里，我们选择群体输出作为抽象形状的参数。为此，我们设计了一个动态平均一致性估计器来估计抽象的形状参数。抽象的形状参数被用来作为群体状态反馈，以产生一个合适的机器人轨迹。我们证明了所提出的控制框架的有效性和鲁棒性，通过提供一组车一样的机器人在机器人和通信链路故障的存在下，协调集体导航的模拟。
英文摘要：
This paper introduces a distributed leaderless swarm formation control framework to address the problem of collectively driving a swarm of robots to track a time-varying formation. The swarm's formation is captured by the trajectory of an abstract shape that circumscribes the convex hull of robots' positions and is independent of the number of robots and their ordering in the swarm. For each robot in the swarm, given global specifications in terms of the trajectory of the abstract shape parameters, the proposed framework synthesizes a control law that steers the swarm to track the desired formation using the information available at the robot's local neighbors. For this purpose, we generate a suitable local reference trajectory that the robot controller tracks by solving the input-output linearization problem. Here, we select the swarm output to be the parameters of the abstract shape. For this purpose, we design a dynamic average consensus estimator to estimate the abstract shape parameters. The abstract shape parameters are used as the swarm state feedback to generate a suitable robot trajectory. We demonstrate the effectiveness and robustness of the proposed control framework by providing the simulation of coordinated collective navigation of a group of car-like robots in the presence of robots and communication link failures.
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