Where to relocate?: Object rearrangement inside cluttered and confined environments for robotic manipulation

TL;DR

This paper introduces an algorithm for optimal object relocation within cluttered, confined environments to efficiently retrieve target objects, reducing actions and time compared to existing methods.

Contribution

It presents a novel approach for planning object placements inside cluttered spaces, improving efficiency and success rates in robotic rearrangement tasks.

Findings

Reduces pick-and-place actions by up to 23.1%.

Decreases total execution time by up to 28.1%.

Achieves higher success rates than baseline methods.

Abstract

We present an algorithm determining where to relocate objects inside a cluttered and confined space while rearranging objects to retrieve a target object. Although methods that decide what to remove have been proposed, planning for the placement of removed objects inside a workspace has not received much attention. Rather, removed objects are often placed outside the workspace, which incurs additional laborious work (e.g., motion planning and execution of the manipulator and the mobile base, perception of other areas). Some other methods manipulate objects only inside the workspace but without a principle so the rearrangement becomes inefficient. In this work, we consider both monotone (each object is moved only once) and non-monotone arrangement problems which have shown to be NP-hard. Once the sequence of objects to be relocated is given by any existing algorithm, our method aims to minimize the number of pick-and-place actions to place the objects until the target becomes accessible. From extensive experiments, we show that our method reduces the number of pick-and-place actions and the total execution time (the reduction is up to 23.1% and 28.1% respectively) compared to baseline methods while achieving higher success rates.