Harmful marine spills, such as algae blooms and oil spills, damage ecosystems and threaten public health tremendously. Hence, an effective spill coverage and removal strategy will play a significant role in environmental protection. In recent years, low-cost water surface robots have emerged as a solution, with their efficacy verified at small scale. However, practical limitations such as connectivity, scalability, and sensing and operation ranges significantly impair their large-scale use. To circumvent these limitations, we propose a novel asymptotic boundary shrink control strategy that enables collective coverage of a spill by autonomous robots featuring customized operation ranges. For each robot, a novel controller is implemented that relies only on local vision sensors with limited vision range. Moreover, the distributedness of this strategy allows any number of robots to be employed without inter-robot collisions. Finally, features of this approach including the convergence of robot motion during boundary shrink control, spill clearance rate, and the capability to work under limited ranges of vision and wireless connectivity are validated through extensive experiments with simulation.

中文翻译：

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多机器人系统的渐近边界收缩控制

有害的海洋泄漏，例如藻类大量繁殖和石油泄漏，会破坏生态系统并极大地威胁公众健康。因此，有效的泄漏覆盖和清除策略将在环境保护中发挥重要作用。近年来，低成本水面机器人已成为一种解决方案，其功效已在小范围内得到验证。然而，连接性、可扩展性以及传感和操作范围等实际限制显着影响了它们的大规模使用。为了规避这些限制，我们提出了一种新颖的渐近边界收缩控制策略，该策略可以通过具有自定义操作范围的自主机器人来集体覆盖泄漏。对于每个机器人，实现了一种新颖的控制器，该控制器仅依赖于具有有限视觉范围的局部视觉传感器。而且，这种策略的分布式允许使用任意数量的机器人而不会发生机器人之间的碰撞。最后，该方法的特征包括边界收缩控制期间机器人运动的收敛、溢出清除率以及在有限的视觉范围和无线连接下工作的能力，通过大量的仿真实验得到验证。