  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.
