Andreas Cord-Landwehr, M. Fischer, Daniel Jung, F. Heide
{"title":"Asymptotically Optimal Gathering on a Grid","authors":"Andreas Cord-Landwehr, M. Fischer, Daniel Jung, F. Heide","doi":"10.1145/2935764.2935789","DOIUrl":null,"url":null,"abstract":"In this paper, we solve the local gathering problem of a swarm of n indistinguishable, point-shaped robots on a two-dimensional grid in asymptotically optimal time O(n) in the fully synchronous FSYNC time model. Given an arbitrarily distributed (yet connected) swarm of robots, the gathering problem on the grid is to locate all robots within a 2 x 2-sized area that is not known beforehand. Two robots are connected if they are vertical or horizontal neighbors on the grid. The locality constraint means that no global control, no compass, no global communication and only local vision is available; hence, a robot can see its grid neighbors only up to a constant L1-distance, which also limits its movements. A robot can move to one of its eight neighboring grid cells and if two or more robots move to the same location they are merged to be only one robot. The locality constraint is the significant challenging issue here, since robot movements must not harm the (only globally checkable) swarm connectivity. For solving the gathering problem, we provide a synchronous algorithm -- executed by every robot -- which ensures that robots merge without breaking the swarm connectivity. In our model, robots can obtain a special state, which marks such a robot to be performing specific connectivity preserving movements in order to allow later merge operations of the swarm. Compared to the grid, for gathering in the Euclidean plane for the same robot and time model the best known upper bound is O(n2).","PeriodicalId":346939,"journal":{"name":"Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2935764.2935789","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26
Abstract
In this paper, we solve the local gathering problem of a swarm of n indistinguishable, point-shaped robots on a two-dimensional grid in asymptotically optimal time O(n) in the fully synchronous FSYNC time model. Given an arbitrarily distributed (yet connected) swarm of robots, the gathering problem on the grid is to locate all robots within a 2 x 2-sized area that is not known beforehand. Two robots are connected if they are vertical or horizontal neighbors on the grid. The locality constraint means that no global control, no compass, no global communication and only local vision is available; hence, a robot can see its grid neighbors only up to a constant L1-distance, which also limits its movements. A robot can move to one of its eight neighboring grid cells and if two or more robots move to the same location they are merged to be only one robot. The locality constraint is the significant challenging issue here, since robot movements must not harm the (only globally checkable) swarm connectivity. For solving the gathering problem, we provide a synchronous algorithm -- executed by every robot -- which ensures that robots merge without breaking the swarm connectivity. In our model, robots can obtain a special state, which marks such a robot to be performing specific connectivity preserving movements in order to allow later merge operations of the swarm. Compared to the grid, for gathering in the Euclidean plane for the same robot and time model the best known upper bound is O(n2).
在完全同步FSYNC时间模型中,我们解决了二维网格上n个不可区分的点型机器人群在渐近最优时间0 (n)下的局部聚集问题。给定一个任意分布(但连接)的机器人群,网格上的聚集问题是在事先未知的2 x 2大小的区域内定位所有机器人。如果两个机器人在网格上垂直或水平相邻,则它们连接在一起。局部性约束意味着没有全局控制,没有指南针,没有全局通信,只有局部视野;因此,机器人只能在恒定的l1距离内看到它的网格邻居,这也限制了它的运动。机器人可以移动到八个相邻网格单元中的一个,如果两个或多个机器人移动到相同的位置,它们将合并为一个机器人。局部性约束在这里是一个具有重大挑战性的问题,因为机器人的运动必须不损害(只有全局可检查的)群体连接。为了解决聚集问题,我们提供了一个同步算法——由每个机器人执行——确保机器人在不破坏群连接的情况下合并。在我们的模型中,机器人可以获得一个特殊的状态,这标志着这样一个机器人正在执行特定的连通性保持运动,以便于以后的群体合并操作。与网格相比,对于同一机器人和时间模型在欧几里得平面上的集合,已知的上界是O(n2)。