On Minimizing the Number of Running Buffers for Tabletop Rearrangement

TL;DR

This paper investigates the minimum number of temporary buffers needed for tabletop rearrangement tasks, proving NP-hardness, unbounded growth in certain cases, and providing scalable algorithms with empirical validation.

Contribution

It introduces a dependency graph approach to determine MRB, proves NP-hardness, and develops scalable algorithms for both labeled and unlabeled rearrangement problems.

Findings

MRB computation is NP-hard.

Number of buffers can grow unbounded with more objects.

Algorithms effectively handle over a hundred objects.

Abstract

For tabletop rearrangement problems with overhand grasps, storage space outside the tabletop workspace, or buffers, can temporarily hold objects which greatly facilitates the resolution of a given rearrangement task. This brings forth the natural question of how many running buffers are required so that certain classes of tabletop rearrangement problems are feasible. In this work, we examine the problem for both the labeled (where each object has a specific goal pose) and the unlabeled (where goal poses of objects are interchangeable) settings. On the structural side, we observe that finding the minimum number of running buffers (MRB) can be carried out on a dependency graph abstracted from a problem instance, and show that computing MRB on dependency graphs is NP-hard. We then prove that under both labeled and unlabeled settings, even for uniform cylindrical objects, the number of required running buffers may grow unbounded as the number of objects to be rearranged increases; we further show that the bound for the unlabeled case is tight. On the algorithmic side, we develop highly effective algorithms for finding MRB for both labeled and unlabeled tabletop rearrangement problems, scalable to over a hundred objects under very high object density. Employing these algorithms, empirical evaluations show that random labeled and unlabeled instances, which more closely mimics real-world setups, have much smaller MRBs.