In distributed computing by mobile robots, robots are deployed over a region, continuous or discrete, operating through a sequence of \textit{look-compute-move} cycles. An extensive study has been carried out to understand the computational powers of different robot models. The models vary on the ability to 1)~remember constant size information and 2)~communicate constant size message. Depending on the abilities the different models are 1)~$\mathcal{OBLOT}$ (robots are oblivious and silent), 2)~$\mathcal{FSTA}$ (robots have finite states but silent), 3)~$\mathcal{FCOM}$ (robots are oblivious but can communicate constant size information) and, 4)~$\mathcal{LUMI}$ (robots have finite states and can communicate constant size information). Another factor that affects computational ability is the scheduler that decides the activation time of the robots. The main three schedulers are \textit{fully-synchronous}, \textit{semi-synchronous} and \textit{asynchronous}. Combining the models ($M$) with schedulers ($K$), we have twelve combinations $M^K$. In the euclidean domain, the comparisons between these twelve variants have been done in different works for transparent robots, opaque robots, and robots with limited visibility. There is a vacant space for similar works when robots are operating on discrete regions like networks. It demands separate research attention because there have been a series of works where robots operate on different networks, and there is a fundamental difference when robots are operating on a continuous domain versus a discrete domain in terms of robots' movement. This work contributes to filling the space by giving a full comparison table for all models with two synchronous schedulers: fully-synchronous and semi-synchronous.

翻译：在移动机器人的分布式计算中，机器人被部署在一个连续或离散的区域上，通过一系列“观察-计算-移动”周期进行操作。已有广泛研究致力于理解不同机器人模型的计算能力。这些模型在以下能力上存在差异：1）记忆常量大小的信息；2）通信常量大小的消息。根据这些能力，不同模型包括：1）$\mathcal{OBLOT}$（机器人是无记忆且静默的）；2）$\mathcal{FSTA}$（机器人具有有限状态但静默）；3）$\mathcal{FCOM}$（机器人无记忆但可通信常量大小的信息）；以及4）$\mathcal{LUMI}$（机器人具有有限状态且可通信常量大小的信息）。另一个影响计算能力的因素是决定机器人激活时间的调度器。三种主要调度器为：完全同步、半同步和异步。将模型（$M$）与调度器（$K$）结合，我们得到十二种组合 $M^K$。在欧几里得域中，已有不同工作针对透明机器人、不透明机器人以及有限可见度机器人，对这十二种变体进行了比较。然而，当机器人在离散区域（如网络）上操作时，类似研究尚属空白。这需要单独的研究关注，因为已有系列工作探讨机器人在不同网络上的操作，且机器人在连续域与离散域中的移动存在根本性差异。本研究通过为所有模型与两种同步调度器（完全同步和半同步）提供完整的比较表，填补了这一空白。