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:本文提出一种新型的分布式覆盖控制器,用于具有常速单车机器人的多智能体系统。该工作是受传统方法的限制启发而来,传统方法不能确保满足硬状态和输入依赖的约束,并导致多常速单车机器人系统出现可行性问题。本文通过设计新的覆盖成本函数和基于饱和梯度搜索的控制器来解决这些问题。不变集理论和基于李雅普诺夫技术用于证明系统的状态相关限制和状态收敛于最优覆盖配置。该控制器是基于智能体之间的新型通信标准实现的分布式方法。进行了一系列仿真案例研究以验证所提出的覆盖控制在不同初始条件和控制参数下的有效性。仿真比较研究揭示了所提出的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实际机器人上的适用性。从理论分析到实验验证的开发过程为具有复杂智能体动态性的多智能体系统坐标控制提供了一种新的框架。