Gathering is a fundamental coordination problem in cooperative mobile robotics. In short, given a set of robots with arbitrary initial locations and no initial agreement on a global coordinate system, gathering requires that all robots, following their algorithm, reach the exact same but not predetermined location. Gathering is particularly challenging in networks where robots are oblivious (i.e., stateless) and direct communication is replaced by observations on their respective locations. Interestingly any algorithm that solves gathering with oblivious robots is inherently self-stabilizing if no specific assumption is made on the initial distribution of the robots. In this paper, we significantly extend the studies of deterministic gathering feasibility under different assumptions related to synchrony and faults (crash and Byzantine). Unlike prior work, we consider a larger set of scheduling strategies, such as bounded schedulers. In addition, we extend our study to the feasibility of probabilistic self-stabilizing gathering in both fault-free and fault-prone environments.

中文翻译：

---

碰撞或拜占庭故障下移动机器人的自稳聚集

收集是协作移动机器人中的一个基本协调问题。简而言之，给定一组具有任意初始位置且在全局坐标系上没有初始协议的机器人，收集要求所有机器人按照其算法到达完全相同但未预先确定的位置。在机器人无意识（即无状态）并且直接通信被对其各自位置的观察所取代的网络中，收集尤其具有挑战性。有趣的是，如果没有对机器人的初始分布做出具体假设，任何解决与不经意机器人收集的算法本质上都是自稳定的。在本文中，我们在与同步和故障（崩溃和拜占庭）相关的不同假设下显着扩展了确定性收集可行性的研究。与之前的工作不同，我们考虑了一组更大的调度策略，例如有界调度程序。此外，我们将研究扩展到在无故障和易发生故障的环境中进行概率自稳定收集的可行性。