ReloPush: Multi-object Rearrangement in Confined Spaces with a Nonholonomic Mobile Robot Pusher

TL;DR

ReloPush is a novel graph-based planning framework enabling a nonholonomic mobile robot to efficiently and robustly perform multi-object rearrangement in cluttered environments by leveraging a unified representation of constraints.

Contribution

The paper introduces the Push-Traversability graph and ReloPush framework, integrating geometric, kinematic, and physics constraints for complex multi-object rearrangement planning.

Findings

ReloPush achieves significantly faster runtimes.

It demonstrates higher robustness in real-world scenarios.

Lower object contact loss compared to baselines.

Abstract

We focus on push-based multi-object rearrangement planning using a nonholonomically constrained mobile robot. The simultaneous geometric, kinematic, and physics constraints make this problem especially challenging. Prior work on rearrangement planning often relaxes some of these constraints by assuming dexterous hardware, prehensile manipulation, or sparsely occupied workspaces. Our key insight is that by capturing these constraints into a unified representation, we could empower a constrained robot to tackle difficult problem instances by modifying the environment in its favor. To this end, we introduce a Push-Traversability graph, whose vertices represent poses that the robot can push objects from, and edges represent optimal, kinematically feasible, and stable transitions between them. Based on this graph, we develop ReloPush, a graph-based planning framework that takes as input a complex multi-object rearrangement task and breaks it down into a sequence of single-object pushing tasks. We evaluate ReloPush across a series of challenging scenarios, involving the rearrangement of densely cluttered workspaces with up to nine objects, using a 1/10-scale robot racecar. ReloPush exhibits orders of magnitude faster runtimes and significantly more robust execution in the real world, evidenced in lower execution times and fewer losses of object contact, compared to two baselines lacking our proposed graph structure.