The ability of intelligent unmanned platforms to achieve autonomous navigation and
positioning in a large-scale environment has become increasingly demanding, in which …

Visual SLAM (VSLAM) has been developing rapidly due to its advantages of low-cost
sensors, the easy fusion of other sensors, and richer environmental information. Traditional …

Parkour is a grand challenge for legged locomotion that requires robots to overcome various
obstacles rapidly in complex environments. Existing methods can generate either diverse …

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

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 …

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 …

Autonomous exploration of subterranean environments constitutes a major frontier for
robotic systems as underground settings present key challenges that can render robot …

In the realm of video object tracking auxiliary modalities such as depth thermal or event data
have emerged as valuable assets to complement the RGB trackers. In practice most existing …

To achieve accurate and robust pose estimation in Simultaneous Localization and Mapping
(SLAM) task, multisensor fusion is proven to be an effective solution and thus provides great …

We present visual inertial lidar legged navigation system (VILENS), an odometry system for
legged robots based on factor graphs. The key novelty is the tight fusion of four different …