Present and Future of SLAM in Extreme Underground Environments

@article{Ebadi2022PresentAF,
  title={Present and Future of SLAM in Extreme Underground Environments},
  author={Kamak Ebadi and Lukas Bernreiter and Harel Biggie and Gavin Catt and Yun Chang and Arghya Chatterjee and Chris Denniston and Simon-Pierre Desch{\^e}nes and Kyle Harlow and Shehryar Khattak and Lucas Nogueira and Matteo Palieri and Pavel Petr'avcek and Matvej Petrl'ik and Andrzej Reinke and V'it Kr'atk'y and Shibo Zhao and Ali-akbar Agha-mohammadi and Kostas Alexis and C. Heckman and Kasra Khosoussi and Navinda Kottege and Benjamin Morrell and Marco Hutter and Fred Pauling and Franccois Pomerleau and Martin Saska and Sebastian A. Scherer and Roland Y. Siegwart and Jason L. Williams and Luca Carlone},
  journal={ArXiv},
  year={2022},
  volume={abs/2208.01787}
}
—This paper surveys recent progress and discusses future opportunities for Simultaneous Localization And Mapping (SLAM) in extreme underground environments. SLAM in subterranean environments, from tunnels, caves, and man-made underground structures on Earth, to lava tubes on Mars, is a key enabler for a range of applications, such as planetary exploration, search and rescue, disaster response, and automated mining, among others. SLAM in underground environments has recently received substantial… 

References

SHOWING 1-10 OF 121 REFERENCES

LAMP 2.0: A Robust Multi-Robot SLAM System for Operation in Challenging Large-Scale Underground Environments

TLDR
This letter reports on a multi-robot SLAM system developed by team CoSTAR in the context of the DARPA Subterranean Challenge, and extends the previous work, LAMP, by incorporating a single-ro Bot front-end interface that is adaptable to different odometry sources and lidar configurations.

LAMP: Large-Scale Autonomous Mapping and Positioning for Exploration of Perceptually-Degraded Subterranean Environments

TLDR
This paper presents a system architecture to enhance subterranean operation, including an accurate lidar-based front-end, and a flexible and robust back-end that automatically rejects outlying loop closures, and discusses potential improvements, limitations of the state of the art, and future research directions.

Three-dimensional Terrain Aware Autonomous Exploration for Subterranean and Confined Spaces

TLDR
A novel three-dimensional autonomous exploration method for ground robots that considers the terrain traversability combined with the frontier expected information gain as a metric for the next best frontier selection in GPS-denied, confined spaces is proposed.

Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age

TLDR
What is now the de-facto standard formulation for SLAM is presented, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers.

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

TLDR
This survey presents a survey of the scientific literature on the topic of Collaborative Simultaneous Localization and Mapping (C- SLAM), also known as multi-robot SLAM, and introduces the basic concepts of C-SLAM and presents a thorough literature review.

Autonomous Search for Underground Mine Rescue Using Aerial Robots

TLDR
A new class of Micro Aerial Vehicles are equipped with the ability to localize and map in subterranean settings, explore unknown mine environments on their own, and perform detection and localization of objects of interest for the purposes of mine rescue.

VI-SLAM for Subterranean Environments

TLDR
This work presents an evaluation of visual-inertial SLAM in the subterranean environment with onboard lighting and shows that it can consistently perform quite well, with less than 4% translational drift.

DARPA Subterranean Challenge: Multi-robotic Exploration of Underground Environments

TLDR
A description of the multi-robot heterogeneous exploration system of the CTU-CRAS team, which scored third place in the Tunnel Circuit round, surpassing the performance of all other non-DARPA-funded competitors.

RMF-Owl: A Collision-Tolerant Flying Robot for Autonomous Subterranean Exploration

TLDR
RMF-Owl is a new collision-tolerant aerial robot tailored for resilient autonomous subterranean exploration with focus on collision tolerance, resilient autonomy with robust localization and mapping, alongside high-performance exploration path planning in confined, obstacle-filled and topologically complex underground environments.

DARE-SLAM: Degeneracy-Aware and Resilient Loop Closing in Perceptually-Degraded Environments

TLDR
A degeneracy-aware and drift-resilient loop closing method to improve place recognition and resolve 3D location ambiguities for simultaneous localization and mapping (SLAM) in GPS-denied, large-scale and perceptually-degraded environments.
...