Avoiding target congestion on the navigation of robotic swarms
Avoiding target congestion on the navigation of robotic swarms
复制标题
避免机器人群导航时出现目标拥堵
DOI：
10.1007/s10514-016-9577-x
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发表时间：
2016
影响因子：
3.5
通讯作者：
L. Chaimowicz
中科院分区：
文献类型：
--
作者：
L. Marcolino;Yuri Tavares dos Passos;Álvaro Antônio Fonseca de Souza;Andersoney dos Santos Rodrigues;L. Chaimowicz
机器人群是由大量机器人组成的分散系统。群体中遇到的一个常见问题是拥塞，因为大量机器人通常必须向同一区域移动。当机器人有共同目标时，例如在觅食或航路点导航期间，就会发生这种情况。我们提出了三种算法来缓解拥塞：第一种算法，一些机器人停止向目标移动，进行随机次数的迭代；在第二个区域中，我们将场景分为两个区域：一个用于向目标移动的机器人，另一个用于离开目标的机器人；在第三种中，我们结合了前面的两种算法。我们在模拟中评估我们的算法，并证明所有这些算法都可以有效地改善导航。此外，我们在现实世界中对十个机器人进行了实验分析，并表明我们所有的方法都以统计显着性改善了导航。
Robotic swarms are decentralized systems formed by a large number of robots. A common problem encountered in a swarm is congestion, as a great number of robots often must move towards the same region. This happens when robots have a common target, for example during foraging or waypoint navigation. We propose three algorithms to alleviate congestion: in the first, some robots stop moving towards the target for a random number of iterations; in the second, we divide the scenario in two regions: one for the robots that are moving towards the target, and another for the robots that are leaving the target; in the third, we combine the two previous algorithms. We evaluate our algorithms in simulation, where we show that all of them effectively improve navigation. Moreover, we perform an experimental analysis in the real world with ten robots, and show that all our approaches improve navigation with statistical significance.