3D LiDAR
3D LiDAR technology uses laser-based rangefinding to create detailed three-dimensional maps of the environment, primarily for applications in robotics and autonomous systems. Current research emphasizes improving accuracy and robustness in challenging conditions (e.g., low light, adverse weather) through sensor fusion (combining LiDAR with cameras or radar), advanced algorithms like deep learning for calibration and object detection, and novel SLAM (Simultaneous Localization and Mapping) techniques incorporating reference maps or other sensor data. These advancements are crucial for enhancing the reliability and safety of autonomous vehicles, robots operating in unstructured environments, and applications such as 3D modeling and mapping for various industries.
Papers
Kinematic-ICP: Enhancing LiDAR Odometry with Kinematic Constraints for Wheeled Mobile Robots Moving on Planar Surfaces
Tiziano Guadagnino, Benedikt Mersch, Ignacio Vizzo, Saurabh Gupta, Meher V.R. Malladi, Luca Lobefaro, Guillaume Doisy, Cyrill Stachniss
A Surface Adaptive First-Look Inspection Planner for Autonomous Remote Sensing of Open-Pit Mines
Vignesh Kottayam Viswanathan, Vidya Sumathy, Christoforos Kanellakis, George Nikolakopoulos
SLAM2REF: Advancing Long-Term Mapping with 3D LiDAR and Reference Map Integration for Precise 6-DoF Trajectory Estimation and Map Extension
Miguel Arturo Vega Torres, Alexander Braun, André Borrmann
BIM-SLAM: Integrating BIM Models in Multi-session SLAM for Lifelong Mapping using 3D LiDAR
Miguel Arturo Vega Torres, Alexander Braun, André Borrmann
TeFF: Tracking-enhanced Forgetting-free Few-shot 3D LiDAR Semantic Segmentation
Junbao Zhou, Jilin Mei, Pengze Wu, Liang Chen, Fangzhou Zhao, Xijun Zhao, Yu Hu