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

Loop closure detection is an essential component of simultaneous localization and map**
(SLAM) systems, which reduces the drift accumulated over time. Over the years, several …

Accurate and robust localization and map** are essential components for most
autonomous robots. In this paper, we propose a simultaneous localization and map** …

Accurate and robust place recognition is essential for robot navigation, yet achieving full
pose invariance and high performance across diverse scenes remains challenging. In this …

Place recognition is crucial for robot localization and loop closure in simultaneous
localization and map** (SLAM). Light Detection and Ranging (LiDAR), known for its …

This paper focuses on the Light Detection and Ranging (LiDAR)–Inertial Measurement Unit
(IMU) simultaneous localization and map** (SLAM) problem: How to fuse the sensor …

Feature extraction and matching are the basic parts of many robotic vision tasks, such as 2D
or 3D object detection, recognition, and registration. As is known, 2D feature extraction and …

Global localization plays a critical role in many robot applications. LiDAR-based global
localization draws the community's focus with its robustness against illumination and …