Autonomous driving (AD), including single-vehicle intelligent AD and vehicle–infrastructure
cooperative AD, has become a current research hot spot in academia and industry, and …

Nowadays, and more than a decade after the first steps towards autonomous driving, we
keep heading to achieve fully autonomous vehicles on our roads, with LiDAR sensors being …

Indoor autonomous navigation refers to the perception and exploration abilities of mobile
agents in unknown indoor environments with the help of various sensors. It is the basic and …

Most sensor setups for onboard autonomous perception are composed of LiDARs and
vision systems, as they provide complementary information that improves the reliability of the …

Determining the extrinsic parameter between multiple light detection and rangings (LiDARs)
and cameras is essential for autonomous robots, especially for solid-state LiDARs, where …

The recent trend of fusing complementary data from LiDARs and cameras for more accurate
perception has made the extrinsic calibration between the two sensors critically important …

Accurate LiDAR-camera online calibration is critical for modern autonomous vehicles and
robot platforms. Dominant methods heavily rely on hand-crafted features, which are not …

In rapidly-evolving domains such as autonomous driving the use of multiple sensors with
different modalities is crucial to ensure high operational precision and stability. To correctly …

Map-centric SLAM utilizes elasticity as a means of loop closure. This approach reduces the
cost of loop closure while still providing large-scale fusion-based dense maps, when …

A system with light detection and ranging (LiDAR) and camera (named as LiDAR-camera
system) plays the essential role in intelligent vehicle (IV), for it provides 3D spatial and 2D …