Exploiting Subgraph Structure in Multi-Robot Path Planning
  Multi-robot path planning is difficult due to the combinatorial explosion of
the search space with every new robot added. Complete search of the combined
state-space soon becomes intractable. In this paper we present a novel form of
abstraction that allows us to plan much more efficiently. The key to this
abstraction is the partitioning of the map into subgraphs of known structure
with entry and exit restrictions which we can represent compactly. Planning
then becomes a search in the much smaller space of subgraph configurations.
Once an abstract plan is found, it can be quickly resolved into a correct (but
possibly sub-optimal) concrete plan without the need for further search. We
prove that this technique is sound and complete and demonstrate its practical
effectiveness on a real map.
  A contending solution, prioritised planning, is also evaluated and shown to
have similar performance albeit at the cost of completeness. The two approaches
are not necessarily conflicting; we demonstrate how they can be combined into a
single algorithm which outperforms either approach alone.
