AIOCMay 21, 2019

Position Paper: From Multi-Agent Pathfinding to Pipe Routing

arXiv:1905.08412v14 citations
Originality Synthesis-oriented
AI Analysis

This work connects theoretical MAPF research to practical industrial applications like pipe routing, though it is incremental in extending existing methods to a new domain.

The paper demonstrates that Multi-Agent Pathfinding (MAPF) algorithms can be applied to the 3D Pipe Routing (PR) problem, showing their performance on abstract instances and opening a new industrial direction.

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.

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