Algorithmic Approaches to Reconfigurable Assembly Systems

TL;DR

This paper explores algorithmic strategies for reconfiguring large-scale space structures using robotics, analyzing different computational paradigms and their impact on scalability, efficiency, and fault tolerance in in-space assembly.

Contribution

It introduces new graph-based abstractions and compares centralized and distributed algorithms for space structure reconfiguration, providing design recommendations.

Findings

Algorithms vary in efficiency for different objectives

Distributed algorithms improve fault tolerance

Design trade-offs impact scalability and performance

Abstract

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.