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

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 …

Simultaneous localization and map** (SLAM) has been widely used in augmented reality
(AR), virtual reality (VR), robotics, and autonomous vehicles as the theoretical basis for …

Place recognition is a critical technology in robot navigation and autonomous driving,
remains challenging due to inefficient point cloud computation, limited feature …

Place recognition, which is also known as loop detection, has been one of the main
problems in the field of robot navigation, and it is crucial in realizing high-performance …

Place recognition is considered as an effective strategy to reduce robot drift errors. In this
work, a place recognition method that uses binary features to match loop closure frames is …

Efficient and precise loop closure detection is essential for both autonomous vehicles and
robotics. Currently, loop closure detection technologies can recognize locations using the …

Simultaneous localization and map** (SLAM) is one of the key technologies for mobile
robots to achieve autonomous driving, and the lidar SLAM algorithm is the mainstream …

Loop detection constitutes an indispensable component in robotics and autonomous driving
navigation systems. Extant literature has predominantly focused on extracting essential …