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MetroLoc: Metro Vehicle Mapping and Localization With LiDAR-Camera-Inertial Integration
In this paper, we propose an accurate and robust multi-modal sensor fusion framework, MetroLoc, towards one of the most extreme scenarios, the large-scale metro environments. MetroLoc is built atop an IMU-centric state estimator that tightly couples light detection and ranging (LiDAR), visual, and inertial information with the convenience of loosely coupled methods. The proposed framework is compo...Show More
Retrieving the 3-D Tropospheric Wet Refractivity Field From a Standalone Ground-Based GNSS Station With A Priori Information: Theory and Simulation
Xianjie Li;Jingna Bai;Jean-Pierre Barriot;Yidong Lou;Weixing Zhang
Sensing water vapor contents in the troposphere with ground-based Global Navigation Satellite System (GNSS) stations has been widely studied and related to extreme weather events and climate changes over the years. Usually, GNSS tomography is the tool of choice to retrieve the 3-D water vapor field. However, a dense GNSS network is required, which means that the GNSS tomography is not applicable e...Show More
A LiDAR-Inertial SLAM Tightly Coupled With Dropout-Tolerant GNSS Fusion for Autonomous Mine Service Vehicles
Yusheng Wang;Yidong Lou;Weiwei Song;Bing Zhan;Feihuang Xia;Qigeng Duan
Multimodal sensor integration has become a crucial prerequisite for real-world navigation systems. Recent studies have reported successful deployment of such systems in many fields. However, it is still challenging for navigation tasks in mine scenes due to satellite signal dropouts, degraded perception, and observation degeneracy. To solve this problem, we propose a light detection and ranging (L...Show More
Accurate, real-time, seamless, and reliable train localization is one of the most critical tasks for automatic train control systems. With the prospect of replacing the traditional track-side infrastructures, independent on-board sensors have attracted a great deal of interest. Since each rail vehicle is equipped with visual cameras, the visual–inertial simultaneous localization and mapping (VI-SL...Show More
LiDAR–Inertial Integration for Rail Vehicle Localization and Mapping in Tunnels
Xinye Dai;Weiwei Song;Yusheng Wang;Yangyang Xu;Yidong Lou;Weiming Tang
Modern light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) systems have delivered excellent results in real-world scenarios. However, the potential of LiDAR SLAM still lacks well investigation for rail vehicle applications. This article proposes an SLAM method for rail vehicles in tunnel environments, which fully exploits the typical geometric feature structure i...Show More
Towards Image-Grade LiDAR Odometry and Mapping
2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)
Year: 2022 | Conference Paper |
The recent developments in LiDAR technologies has promoted several super high intensity image-grade LiDAR sensors, receiving great interest in the intelligent transportation applications. Although objects detection and high-resolution map construction can benefit from this characteristic, there are several underlying challenges arising from such LiDARs. In this contribution, we present a robust an...Show More
Rail Vehicle Localization and Mapping With LiDAR-Vision-Inertial-GNSS Fusion
Yusheng Wang;Weiwei Song;Yidong Lou;Yi Zhang;Fei Huang;Zhiyong Tu;Qiangsheng Liang
In this letter, 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-V is formulated atop a factor graph and consists of two subsystems: an odometer assisted LiDAR-inertial system (OLIS) and an odometer integrated Visual-inertial system (OVIS). Both the subsystem exploits the...Show More
Simultaneous Localization of Rail Vehicles and Mapping of Environment With Multiple LiDARs
Yusheng Wang;Weiwei Song;Yidong Lou;Fei Huang;Zhiyong Tu;Shimin Zhang
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 simultaneous localization and mapping (SLAM) system for railway applications. Our approach starts with measurements preprocessing to denoise and synchronize multiple LiDAR inputs. Different frame-to-frame registration methods are u...Show More
Simultaneous Localization of Rail Vehicles and Mapping of Surroundings With LiDAR-Inertial-GNSS Integration
Yusheng Wang;Yidong Lou;Weiwei Song;Zhiyong Tu;Yapeng Wang;Shimin Zhang
Accurate rail vehicle positioning is crucial for railroad operational safety. Modern light detection and ranging (LiDAR) simultaneously localization and mapping (SLAM) systems have delivered excellent results in real-world scenarios. However, it still lacks well investigation for rail vehicle applications. In this paper, we propose to achieve real-time accurate and robust positioning and mapping f...Show More
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 autonomous vehicles. Since single LiDAR suffers from hardware failure and performance degradation intermittently, we present a multi-LiDAR integration scheme in this article. Our framework tightly couples multiple non-repeti...Show More
Optimization strategy of satellite maneuvering time based on the performance of system service for BDS
Caibo Hu;Chuang Shi;Jinping Chen;Yidong Lou;Zhixue Zhang;Jinxian Zhao
Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference
Year: 2014 | Conference Paper |
The paper presents a method by sliding window to find an optimal satellite maneuvering time with analyzing the change of constellation geometry at different time. Navigation satellites not only broadcast the signals, the orbits and clock corrections etc., but also keep an in-view constellation, which are the factors affecting users to calculate position. Effected by orbit perturbations, the satell...Show More
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