多连通水面舰艇的分布式运动控制
Distributed Motion Control for Multiple Connected Surface Vessels
摘要：
我们提出了一种可扩展的合作控制方法，协调一组刚性连接的自主水面船舶跟踪所需的轨迹在平面水环境作为一个单一的浮动模块化结构。我们的方法利用隐含的信息结构的运动力和扭矩分配没有明确的机器人之间的通信。在我们的系统中，领导者机器人通过根据结构与期望轨迹的偏差调整其力和扭矩来引导整个组，而跟随者机器人运行基于分布式共识的控制器来匹配它们的输入，以放大领导者的意图，仅使用板载传感器作为反馈。为了应对复杂和高度耦合的系统动力学在水中，领导者机器人采用非线性模型预测控制器（NMPC），在那里我们实验估计的浮动模块化结构的动力学模型，以实现卓越的性能，领导者跟随控制。我们的方法在当今许多现有水道中运输人员和货物方面具有广泛的潜在应用。我们进行了轨迹和方向跟踪实验的硬件与三个定制的自主模块化机器人船，称为Roboat，这是能够完整的运动和板载状态估计。多达65个机器人的仿真结果也证明了我们所提出的方法的可扩展性。
英文摘要：
We propose a scalable cooperative control approach which coordinates a group of rigidly connected autonomous surface vessels to track desired trajectories in a planar water environment as a single floating modular structure. Our approach leverages the implicit information of the structure's motion for force and torque allocation without explicit communication among the robots. In our system, a leader robot steers the entire group by adjusting its force and torque according to the structure's deviation from the desired trajectory, while follower robots run distributed consensus-based controllers to match their inputs to amplify the leader's intent using only onboard sensors as feedback. To cope with the complex and highly coupled system dynamics in the water, the leader robot employs a nonlinear model predictive controller (NMPC), where we experimentally estimated the dynamics model of the floating modular structure in order to achieve superior performance for leader-following control. Our method has a wide range of potential applications in transporting humans and goods in many of today's existing waterways. We conducted trajectory and orientation tracking experiments in hardware with three custom-built autonomous modular robotic boats, called Roboat, which are capable of holonomic motions and onboard state estimation. Simulation results with up to 65 robots also prove the scalability of our proposed approach.
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