Present and Future of SLAM in Extreme Underground Environments

  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},
—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… 

Extrinsic calibration for highly accurate trajectories reconstruction

—In the context of robotics, accurate ground-truth positioning is the cornerstone for the development of mapping and localization algorithms. In outdoor environments and over long distances, total

Virtual Reality via Object Poses and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabilities

A novel telepresence system for advancing aerial manipulation in dynamic and unstructured environments that not only features a haptic device, but also a virtual reality (VR) interface that provides real-time 3D displays of the robot’s workspace as well as a haaptic guidance to its remotely located operator.

PyPose: A Library for Robot Learning with Physics-based Optimization

The design goal for PyPose is to make it user-friendly,cient, and interpretable with a tidy and well-organized architecture, and it can be easily integrated into real-world robotic applications.

X-ICP: Localizability-Aware LiDAR Registration for Robust Localization in Extreme Environments

The proposed framework demonstrates accurate and generalizable localizability detection and robust pose estimation without environment-specific parameter tuning and underlying the gain in performance and reliability in LiDAR-challenging scenarios.



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

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

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

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

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

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

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

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.

Online 3D Frontier-Based UGV and UAV Exploration Using Direct Point Cloud Visibility

This paper presents a new approach that addresses the complexity of operating in 3D by directly modelling the boundary between observed free and unobserved space (the frontier), rather than utilising dense 3D volumetric representations.

An autonomous unmanned aerial vehicle system for fast exploration of large complex indoor environments

This paper introduces an autonomous system employing multirotor unmanned aerial vehicles for fast 3D exploration and inspection of vast, unknown, dynamic, and complex environments containing large

DARPA Subterranean Challenge: Multi-robotic Exploration of Underground Environments

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.