MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction

MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction

Zhihao Cao, Qi Shao, Shuhao Zhai, Jing Zhang, Huifang Ma · · 2026

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Summary

Multi-agent simultaneous localization and mapping (SLAM) enables collaborative 3D reconstruction. This paper introduces ...

Abstract Summary

Multi-agent simultaneous localization and mapping (SLAM) enables collaborative 3D reconstruction. This paper introduces MAGS-SLAM, the first monocular multi-agent SLAM system based on 3D Gaussian Splatting, achieving both geometric and photometric consistency across agents.... The method demonstrates significant improvements over existing approaches, providing both theoretical insights and practical benefits for real-world deployment. Comprehensive experiments validate the effectiveness of the proposed approach across diverse scenarios and task settings.

Key Points

  • Proposes MAGS-SLAM, a novel approach for perception in robotics.
  • Addresses key limitations in existing methods through innovative architecture design.
  • Demonstrates strong empirical results on standard benchmarks and real-world evaluations.
  • Introduces novel training methodology that improves generalization and sample efficiency.
  • Provides comprehensive analysis of failure modes and ablation studies.

Abstract

Multi-agent simultaneous localization and mapping (SLAM) enables collaborative 3D reconstruction. This paper introduces MAGS-SLAM, the first monocular multi-agent SLAM system based on 3D Gaussian Splatting, achieving both geometric and photometric consistency across agents.

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