This paper proposes a novel distributed coverage controller for a multi-agent system with constant-speed unicycle robots (CSUR). The work is motivated by the limitation of the conventional method that does not ensure the satisfaction of hard state- and input-dependent constraints and leads to feasibility issues for multi-CSUR systems. In this paper, we solve these problems by designing a novel coverage cost function and a saturated gradient-search-based control law. Invariant set theory and Lyapunov-based techniques are used to prove the state-dependent confinement and the convergence of the system state to the optimal coverage configuration, respectively. The controller is implemented in a distributed manner based on a novel communication standard among the agents. A series of simulation case studies are conducted to validate the effectiveness of the proposed coverage controller in different initial conditions and with control parameters. A comparison study in simulation reveals the advantage of the proposed method in terms of avoiding infeasibility. The experiment study verifies the applicability of the method to real robots with uncertainties. The development procedure of the method from theoretical analysis to experimental validation provides a novel framework for multi-agent system coordinate control with complex agent dynamics.

翻译：本文提出了一种针对匀速独轮车机器人（CSUR）多智能体系统的新型分布式覆盖控制器。本工作的动机在于传统方法无法保证满足硬状态约束和输入相关约束，从而导致多CSUR系统存在可行性问题。为解决这些问题，本文设计了一种新型覆盖代价函数和基于饱和梯度搜索的控制律。利用不变集理论和基于李雅普诺夫的技术，分别证明了状态相关约束的保持以及系统状态向最优覆盖配置的收敛性。该控制器基于智能体间的新型通信标准以分布式方式实现。通过一系列仿真案例研究，验证了所提覆盖控制器在不同初始条件和控制参数下的有效性。仿真中的对比研究揭示了该方法在避免不可行性方面的优势。实验研究验证了该方法在存在不确定性的真实机器人上的适用性。该方法从理论分析到实验验证的开发过程，为具有复杂智能体动力学的多智能体系统协调控制提供了一种新型框架。