论文标题
可重新配置系统的算法方法
Algorithmic Approaches to Reconfigurable Assembly Systems
论文作者
论文摘要
大规模结构系统在空间中的组装被认为对于无法在单个发射中部署的应用程序至关重要。最近的文献建议将离散模块化结构用于空间组装和相对较小的规模机器人技术,这些机器人能够修改和穿越结构。本文解决了通过机器人结构构建的可重新配置空间结构的算法问题,其中重新配置定义为将初始结构转换为不同的目标配置的问题。我们分析了不同的算法范例,并提出了相应的抽象和图形公式,研究了考虑离散的空间和时间步骤的专业算法。然后,我们讨论不同计算体系结构(例如集中式和分布式)的基本设计交易,并将两种代表性算法作为具体示例进行比较。我们分析了这些算法如何实现不同的目标功能和目标,例如最小化总距离,最大化断层耐受性或最小化组装中所花费的总时间。这是为了对相应结构和机器人设计的可扩展性产生算法约束的印象。从这项研究中,就在何时何地使用每个范式以及对物理机器人和结构系统设计的含义提出了一组建议。
Assembly of large scale structural systems in space is understood as critical to serving applications that cannot be deployed from a single launch. Recent literature proposes the use of discrete modular structures for in-space assembly and relatively small scale robotics that are able to modify and traverse the structure. This paper addresses the algorithmic problems in scaling reconfigurable space structures built through robotic construction, where reconfiguration is defined as the problem of transforming an initial structure into a different goal configuration. We analyze different algorithmic paradigms and present corresponding abstractions and graph formulations, examining specialized algorithms that consider discretized space and time steps. We then discuss fundamental design trades for different computational architectures, such as centralized versus distributed, and present two representative algorithms as concrete examples for comparison. We analyze how those algorithms achieve different objective functions and goals, such as minimization of total distance traveled, maximization of fault-tolerance, or minimization of total time spent in assembly. This is meant to offer an impression of algorithmic constraints on scalability of corresponding structural and robotic design. From this study, a set of recommendations is developed on where and when to use each paradigm, as well as implications for physical robotic and structural system design.