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

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

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

classification cs.RO
keywords c-slamcollaborativesurveyapplicationscurrentliteraturelocalizationmapping
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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Cited by 1 Pith paper

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

  1. MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality

    cs.RO 2026-05 unverdicted novelty 4.0

    MR-SLAM combines passthrough mixed reality with multi-robot SLAM on ROS 2 to let one operator supervise mapping in situ, reporting 8.83 Hz scans, 17.9 m² coverage, and 94.7% occupancy consistency in simulated sessions.