Pith. sign in

REVIEW 2 cited by

ORLA*: Mobile Manipulator-Based Object Rearrangement with Lazy A Star

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2309.13707 v2 pith:TEUKEY7Q submitted 2023-09-24 cs.RO cs.AIcs.LG

Kai Gao , Zhaxizhuoma , Yan Ding , Shiqi Zhang , Jingjin Yu This is my paper · ORCID
classification cs.ROcs.AIcs.LG
keywords orlarearrangementmobileobjectobjectsconsideringeffectivelylazy
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Effectively performing object rearrangement is an essential skill for mobile manipulators, e.g., setting up a dinner table or organizing a desk. A key challenge in such problems is deciding an appropriate manipulation order for objects to effectively untangle dependencies between objects while considering the necessary motions for realizing the manipulations (e.g., pick and place). To our knowledge, computing time-optimal multi-object rearrangement solutions for mobile manipulators remains a largely untapped research direction. In this research, we propose ORLA*, which leverages delayed (lazy) evaluation in searching for a high-quality object pick and place sequence that considers both end-effector and mobile robot base travel. ORLA* also supports multi-layered rearrangement tasks considering pile stability using machine learning. Employing an optimal solver for finding temporary locations for displacing objects, ORLA* can achieve global optimality. Through extensive simulation and ablation study, we confirm the effectiveness of ORLA* delivering quality solutions for challenging rearrangement instances. Supplementary materials are available at: https://gaokai15.github.io/ORLA-Star/

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Hume: Introducing System-2 Thinking in Visual-Language-Action Model

    cs.RO 2025-05 conditional novelty 6.0 of 10

    A dual-system vision-language-action model that improves robot control by ranking multiple sampled action chunks with a learned value function before fast execution.

  2. Mobile Manipulation Planning for Tabletop Rearrangement

    cs.RO 2025-05 conditional novelty 6.0 of 10

    STRAP V2 lets a mobile manipulator perform multiple pick-and-place operations from one base position and uses state re-exploration to reduce total cost and planning time in simulated tabletop rearrangement.

Pith tools