  The 2D Multi-Agent Path Finding (MAPF) problem aims at finding collision-free
paths for a number of agents, from a set of start locations to a set of goal
positions in a known 2D environment. MAPF has been studied in theoretical
computer science, robotics, and artificial intelligence over several decades,
due to its importance for robot navigation. It is currently experiencing
significant scientific progress due to its relevance in automated warehousing
(such as those operated by Amazon) and in other contemporary application areas.
In this paper, we demonstrate that many recently developed MAPF algorithms
apply more broadly than currently believed in the MAPF research community. In
particular, we describe the 3D Pipe Routing (PR) problem, which aims at placing
collision-free pipes from given start locations to given goal locations in a
known 3D environment. The MAPF and PR problems are similar: a solution to a
MAPF instance is a set of blocked cells in x-y-t space, while a solution to the
corresponding PR instance is a set of blocked cells in x-y-z space. We show how
to use this similarity to apply several recently developed MAPF algorithms to
the PR problem, and discuss their performance on abstract PR instances. We also
discuss further research necessary to tackle real-world pipe-routing instances
of interest to industry today. This opens up a new direction of industrial
relevance for the MAPF research community.
