This article surveys recent progress and discusses future opportunities for simultaneous
localization and mapping (SLAM) in extreme underground environments. SLAM in …

This paper reports on the state of the art in underground SLAM by discussing different SLAM
strategies and results across six teams that participated in the three-year-long SubT …

The robustness of 3D perception systems under natural corruptions from environments and
sensors is pivotal for safety-critical applications. Existing large-scale 3D perception datasets …

Aggressive motions from agile flights or traversing irregular terrain induce motion distortion
in LiDAR scans that can degrade state estimation and mapping. Some methods exist to …

Challenges inherent to autonomous wintertime navigation in forests include lack of reliable
a Global Navigation Satellite System (GNSS) signal, low feature contrast, high illumination …

Under rapid motion conditions, such as high-speed and vigorous angular velocity, motion
distortion in light detection and ranging (LiDAR) point cloud will be severe and reduce the …

We propose a novel angular velocity estimation method to increase the robustness of
Simultaneous Localization And Mapping (SLAM) algorithms against gyroscope saturations …

This paper presents Direct LiDAR-Inertial Odometry and Mapping (DLIOM), a robust SLAM
algorithm with an explicit focus on computational efficiency, operational reliability, and real …

In this paper, we focus on improving planning efficiency for ground vehicles in navigation
and exploration tasks where the environment is unknown or partially known, leading to …

Autonomous navigation and multi-robot exploration framework for ground robots are key
parts of the robotic system deployed by the team CTU-CRAS-NORLAB in the final event of …