Rapid and robust large-scale SLAM mapping

Determine algorithmic and system-level approaches for Simultaneous Localization and Mapping (SLAM) that enable rapid and robust mapping of large-scale environments, overcoming the limitations observed in single-agent SLAM systems.

Background

The paper motivates multi-robot collaborative SLAM by noting that single-agent SLAM, despite significant progress, struggles to efficiently and reliably map large-scale environments. This limitation is particularly evident in complex real-world scenarios such as urban driving and large-area exploration where scalability, robustness, and global consistency are crucial.

The survey positions 3D Gaussian Splatting (3DGS) as a promising explicit representation for high-fidelity, real-time mapping, and discusses how collaborative multi-agent systems could address the scalability and robustness challenges. However, the fundamental problem of achieving rapid and robust large-scale mapping remains open, motivating research into architectures, data fusion, communication strategies, and consistency mechanisms.

References

While single-agent SLAM has seen remarkable progress, the task of mapping large-scale environments quickly and robustly remains an open problem.

A Survey on Collaborative SLAM with 3D Gaussian Splatting  (2510.23988 - Xuan et al., 28 Oct 2025) in Introduction (Section 1)

It is therefore unclear whether global SLAM optimization actually limits drift in this setting.

Evaluation of Monocular SLAM Systems on High-Altitude Nadir UAV Footage  (2608.18632 - Spagnolo et al., 19 Aug 2026) in Section 1, Introduction

Despite these successes, achieving reliable and efficient performance in large-scale underground environments remains an open challenge, primarily due to the limitations of onboard computation and memory required for autonomous operation.

SUPER ODOMETRY 2.0: Resilient Odometry via Hierarchical Adaptation  (2608.25427 - Zhao et al., 26 Aug 2026) in Supplementary Materials, section “Experiments,” subsection “DARPA Subterranean Challenge”