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 …

The DARPA Subterranean Challenge was designed for competitors to develop and deploy
teams of autonomous robots to explore difficult unknown underground environments …

This paper proposes free-space motion tubes, a motion primitive for the local navigation of
mobile robots equipped with range sensors. The geometry of a candidate motion tube …

Autonomous robots are prone to fail in real world environments, where unknown factors can
cause their world model to be inaccurate or incomplete. This causes robots to become stuck …

As mobile robots become useful performing everyday tasks in complex real-world
environments, they must be able to traverse a range of difficult terrain types such as stairs …

Land vehicles are commonly used in robotics. Most studies consider the types of vehicles
that do not slip easily or develop ways to detect and avoid slippage. This is for multiple …

We investigate the effect of using human demonstration data in the replay buffer for Deep
Reinforcement Learning. We use a policy gradient method with a modified experience …

Regardless of the amount of testing, autonomous mobile robots deployed into unknown
environments will fail at some point. This is because there are unknown factors in the …