We present algorithms for uniformly covering an unknown indoor region with a swarm of simple, anonymous and autonomous mobile agents. The exploration of such regions is made difficult by the lack of a common global reference frame, severe degradation of radio-frequency communication, and numerous ground obstacles. We propose addressing these challenges by using airborne agents, such as Micro Air Vehicles, in dual capacity, both as mobile explorers and (once they land) as beacons that help other agents navigate the region. The algorithms we propose are designed for a swarm of simple, identical, ant-like agents with local sensing capabilities. The agents enter the region, which is discretized as a graph, over time from one or more entry points and are tasked with occupying all of its vertices. Unlike many works in this area, we consider the requirement of informing an outside operator with limited information that the coverage mission is complete. Even with this additional requirement we show, both through simulations and mathematical proofs, that the dual role concept results in linear-time termination, while also besting many well-known algorithms in the literature in terms of energy use.
翻译:我们提出了统一覆盖一个未知室内区域的算法,其范围是一大批简单、匿名和自主的移动物剂。由于缺乏一个共同的全球参照框架,无线电频率通信严重退化,以及许多地面障碍,因此很难对这些地区进行探索。我们提议通过使用航空物剂,例如微型航空飞行器,作为移动探险家和(一旦它们着陆)作为帮助其他物剂在该区域航行的灯塔,来应对这些挑战。我们提议的算法是为一组简单、相同、具有当地感知能力的蚂蚁类物剂设计的。这些物剂进入该区域,从一个或多个入境点分解成一个图表,经过一段时间,并负责占据其所有脊椎。与该领域许多工作不同,我们考虑要求向信息有限、任务完成的外部经营者通报。即使我们通过模拟和数学证据表明这一额外要求,双重作用概念也会导致线性时间的终止,同时在能源使用方面使文献中的许多著名算法成为最佳。