Pith. sign in

REVIEW 3 cited by

Towards Collaborative Simultaneous Localization and Mapping: a Survey of the Current Research Landscape

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 2108.08325 v2 pith:7D4OMZJF submitted 2021-08-18 cs.RO

Pierre-Yves Lajoie , Benjamin Ramtoula , Fang Wu , Giovanni Beltrame This is my paper · ORCID
classification cs.RO
keywords c-slamcollaborativesurveyapplicationscurrentliteraturelocalizationmapping
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

Motivated by the tremendous progress we witnessed in recent years, this paper presents a survey of the scientific literature on the topic of Collaborative Simultaneous Localization and Mapping (C-SLAM), also known as multi-robot SLAM. With fleets of self-driving cars on the horizon and the rise of multi-robot systems in industrial applications, we believe that Collaborative SLAM will soon become a cornerstone of future robotic applications. In this survey, we introduce the basic concepts of C-SLAM and present a thorough literature review. We also outline the major challenges and limitations of C-SLAM in terms of robustness, communication, and resource management. We conclude by exploring the area's current trends and promising research avenues.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 3 Pith papers

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

  1. Strategic Sacrifice: Self-Organized Robot Swarm Localization for Inspection Productivity

    cs.RO 2024-11 conditional novelty 6.0 of 10

    An adaptive robot swarm can increase inspection productivity by self-organizing a few robots into dedicated localizers whose interactions keep the rest of the swarm on task.

  2. MAC-Ego3D: Multi-Agent Gaussian Consensus for Real-Time Collaborative Ego-Motion and Photorealistic 3D Reconstruction

    cs.CV 2024-12 conditional novelty 5.0 of 10

    A multi-agent SLAM system aligns and jointly optimizes shared 3D Gaussian maps to achieve real-time collaborative photorealistic reconstruction with state-of-the-art accuracy.

  3. A Monocular SLAM-based Multi-User Positioning System with Image Occlusion in Augmented Reality

    cs.HC 2024-11 conditional novelty 4.0 of 10

    Multi-user AR positioning is achieved by aligning each user's SLAM map to a common table plane, with MiDaS monocular depth estimation for occlusion rendering.

Pith tools