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 …

Search and rescue with a team of heterogeneous mobile robots in unknown and large-scale
underground environments requires high-precision localization and mapping. This crucial …

3D spatial perception is the problem of building and maintaining an actionable and
persistent representation of the environment in real-time using sensor data and prior …

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 …

Localization and mapping with heterogeneous multisensor fusion have been prevalent in
recent years. To adequately fuse multimodal sensor measurements received at different time …

This paper revisits Kimera-Multi, a distributed multi-robot Simultaneous Localization and
Mapping (SLAM) system, towards the goal of deployment in the real world. In particular, this …

Odometry is crucial for robot navigation, particularly in situations where global positioning
methods like global positioning system are unavailable. The main goal of odometry is to …

LiDAR mapping is important yet challenging in self-driving and mobile robotics. To tackle
such a global point cloud registration problem, DeepMapping converts the complex map …

Artificial perception for robots operating in outdoor natural environments, including forest
scenarios, has been the object of a substantial amount of research for decades. Regardless …