22 citations · 46 across the 11 of their papers we have counts for
9 papers · 1 filter
Four years of multi-modal odometry and mapping on the rail vehicles
Yusheng Wang, Weiwei Song, Yi Zhang +5
Precise, seamless, and efficient train localization as well as long-term railway environment monitoring is the essential property towards reliability, availability, maintainability…
A LiDAR-Inertial SLAM Tightly-Coupled with Dropout-Tolerant GNSS Fusion for Autonomous Mine Service Vehicles
Yusheng Wang, Yidong Lou, Weiwei Song +3
Multi-modal sensor integration has become a crucial prerequisite for the real-world navigation systems. Recent studies have reported successful deployment of such system in many fi…
Motion Degeneracy in Self-supervised Learning of Elevation Angle Estimation for 2D Forward-Looking Sonar
Yusheng Wang, Yonghoon Ji, Chujie Wu +3
2D forward-looking sonar is a crucial sensor for underwater robotic perception. A well-known problem in this field is estimating missing information in the elevation direction duri…
2D Forward Looking Sonar Simulation with Ground Echo Modeling
Yusheng Wang, Chujie Wu, Yonghoon Ji +3
Imaging sonar produces clear images in underwater environments, independent of water turbidity and lighting conditions. The next generation 2D forward looking sonars are compact in…
Simultaneous Location of Rail Vehicles and Mapping of Environment with Multiple LiDARs
Yusheng Wang, Weiwei Song, Yidong Lou +3
Precise and real-time rail vehicle localization as well as railway environment monitoring is crucial for railroad safety. In this letter, we propose a multi-LiDAR based simultaneou…
Rail Vehicle Localization and Mapping with LiDAR-Vision-Inertial-GNSS Fusion
Yusheng Wang, Weiwei Song, Yidong Lou +4
In this paper, we present a global navigation satellite system (GNSS) aided LiDAR-visual-inertial scheme, RailLoMer-V, for accurate and robust rail vehicle localization and mapping…
RailLoMer: Rail Vehicle Localization and Mapping with LiDAR-IMU-Odometer-GNSS Data Fusion
Yusheng Wang, Yidong Lou, Yi Zhang +4
We present RailLoMer in this article, to achieve real-time accurate and robust odometry and mapping for rail vehicles. RailLoMer receives measurements from two LiDARs, an IMU, trai…
MetroLoc: Metro Vehicle Mapping and Localization with LiDAR-Camera-Inertial Integration
Yusheng Wang, Weiwei Song, Yi Zhang +3
We propose an accurate and robust multi-modal sensor fusion framework, MetroLoc, towards one of the most extreme scenarios, the large-scale metro vehicle localization and mapping.…
GM-Livox: An Integrated Framework for Large-Scale Map Construction with Multiple Non-repetitive Scanning LiDARs
Yusheng Wang, Yidong Lou, Weiwei Song +2
With the ability of providing direct and accurate enough range measurements, light detection and ranging (LiDAR) is playing an essential role in localization and detection for auto…