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

Agricultural multirobot systems (MRSs) are expected to be essential in future agriculture.
Therefore, MRSs comprising an aerial robot, a ground robot, and a manipulator are being …

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

Field robotics in perceptually-challenging environments require fast and accurate state
estimation, but modern LiDAR sensors quickly overwhelm current odometry algorithms. To …

We propose Super Odometry, a high-precision multi-modal sensor fusion framework,
providing a simple but effective way to fuse multiple sensors such as LiDAR, camera, and …

LiDAR-based SLAM may easily fail in adverse weathers (eg, rain, snow, smoke, fog), while
mmWave Radar remains unaffected. However, current researches are primarily focused on …

This paper serves as one of the first efforts to enable large-scale and long-duration
autonomy using the Boston Dynamics Spot robot. Motivated by exploring extreme …

A reliable odometry source is a prerequisite to enable complex autonomy behaviour in next-
generation robots operating in extreme environments. In this work, we present a high …

LiDAR has gained popularity in autonomous driving due to advantages like long
measurement distance, rich three-dimensional information, and stability in harsh …