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Integrating V-SLAM and LiDAR-based SLAM for Map Updating
2021 IEEE 4th International Conference on Knowledge Innovation and Invention (ICKII), 2021Vehicle positioning generally uses the global navigation satellite system (GNSS), but systems of different levels significantly affect positioning accuracy. Moreover, it is greatly affected by weather that may cause inaccurate positioning due to excessive cloud cover.
Yu-Cheng Chang +4 more
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EIL‐SLAM: Depth‐enhanced edge‐based infrared‐LiDAR SLAM
Journal of Field Robotics, 2021AbstractTraditional simultaneous localization and mapping (SLAM) approaches that utilize visible cameras or light detection and rangings (LiDARs) frequently fail in dusty, low‐textured, or completely dark environments. To address this problem, this study proposes a novel approach by tightly coupling perception data from a thermal infrared camera and a ...
Wenqiang Chen +3 more
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GLO-SLAM: a slam system optimally combining GPS and LiDAR odometry
Industrial Robot: the international journal of robotics research and application, 2021Purpose Large-scale and precise three-dimensional (3D) map play an important role in autonomous driving and robot positioning. However, it is difficult to get accurate poses for mapping. On one hand, the global positioning system (GPS) data are not always reliable owing to multipath effect and poor satellite visibility in many urban environments.
Ruihao Lin +2 more
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The LIDAR Odometry in the SLAM
2018 23rd Conference of Open Innovations Association (FRUCT), 2018This paper describes an algorithm that performs an contur analyzing of an environment with a single 2D Laser Imaging Detection and Ranging (LIDAR) sensor, as well as its implementation on a mobile platform using the Robot Operating System (ROS). The review of standard sensors shortcomings is provided in article.
Vasilii Kirnos +3 more
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DL-SLAM: Direct 2.5D LiDAR SLAM for Autonomous Driving
2019 IEEE Intelligent Vehicles Symposium (IV), 2019Precisely localizing a vehicle in the GNSS-denied urban area is crucial for autonomous driving. The occupancy grid-based 2D LiDAR SLAM methods scale poorly to outdoor road scenarios, while the 3D point cloud-based LiDAR SLAM methods suffer from huge computation and storage costs.
Jun Li +5 more
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LiDAR SLAM With Plane Adjustment for Indoor Environment
IEEE Robotics and Automation Letters, 2021Planes ubiquitously exist in the indoor environment. This letter presents a real-time and low-drift LiDAR SLAM system using planes as the landmark for the indoor environment. Our algorithm includes three components: localization, local mapping and global mapping. The localization component performs real-time and global registration, instead of the scan-
Lipu Zhou, Daniel Koppel, Michael Kaess
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DVL-SLAM: sparse depth enhanced direct visual-LiDAR SLAM
Autonomous Robots, 2019This paper presents a framework for direct visual-LiDAR SLAM that combines the sparse depth measurement of light detection and ranging (LiDAR) with a monocular camera. The exploitation of the depth measurement between two sensor modalities has been reported in the literature but mostly by a keyframe-based approach or by using a dense depth map.
Young-Sik Shin +2 more
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