论文标题
PAIMBOT：由配对机器人组成的自动移动机器人系统的新型模型
Pairbot: A Novel Model for Autonomous Mobile Robot Systems Consisting of Paired Robots
论文作者
论文摘要
可编程物质（PM）是一种能够通过可编程手段动态改变其物理特性（例如形状或密度）的物质形式。从机器人的角度来看，PM可以实现为由许多小型计算实体组成的分布式系统，以实现特定目标。尽管自动移动机器人系统是一个重要的例子，并且已经进行了二十多年的研究，但这些机器人通常无法执行基本任务，从而揭示了PM实施中的差距。在本文中，我们引入了一种新型的计算范式，称为配对机器人模型（Pairbot模型），该模型是在自主移动机器人系统上构建的。在此模型中，每个机器人与另一个机器人形成一对，使他们能够互相识别并调整其位置以实现指定目标。与传统的LCM型模型相比，即使在异步调度程序条件下，这种配对的基本原理与传统的LCM型模型相比，相比之下，可以显着提高机器人间连接性。这种转变对计算能力，特别是问题的解决性具有相当大的意义。我们探讨了两个具体的挑战 - 永久行进问题和7磅的收集问题 - 以演示PAIMBOT模型的计算能力。该模型提供了新的途径和见解，以解决自动移动机器人中固有的问题。
Programmable matter (PM) is a form of matter capable of dynamically altering its physical properties, such as shape or density, through programmable means. From a robotics perspective, PM can be realized as a distributed system consisting of numerous small computational entities working collaboratively to achieve specific objectives. Although autonomous mobile robot systems serve as an important example and have been researched for more than two decades, these robots often fail to perform even basic tasks, revealing a considerable gap in PM implementation. In this paper, we introduce a novel computational paradigm, termed the Pairing Robot model (Pairbot model), which is built on an autonomous mobile robot system. In this model, each robot forms a pair with another, enabling them to recognize each other and adapt their positions to achieve designated goals. This fundamental principle of pairing substantially enhances inter-robot connectivity compared to conventional LCM-type model, even under asynchronous scheduler conditions. This shift has considerable implications for computational capabilities, specifically in problem solvability. We explore two specific challenges -- the perpetual marching problem and the 7-pairbots-gathering problem -- to demonstrate the computational power of Pairbot model. This model provides new avenues and insights to address inherent issues in autonomous mobile robots.
