194 citations · 316 across the 13 of their papers we have counts for
13 papers
FF-LINS: A Consistent Frame-to-Frame Solid-State-LiDAR-Inertial State Estimator
Hailiang Tang, Tisheng Zhang, Xiaoji Niu +3
Most of the existing LiDAR-inertial navigation systems are based on frame-to-map registrations, leading to inconsistency in state estimation. The newest solid-state LiDAR with a no…
PO-VINS: An Efficient and Robust Pose-Only Visual-Inertial State Estimator With LiDAR Enhancement
Hailiang Tang, Tisheng Zhang, Liqiang Wang +2
The pose adjustment (PA) with a pose-only visual representation has been proven equivalent to the bundle adjustment (BA), while significantly improving the computational efficiency…
Wheel-SLAM: Simultaneous Localization and Terrain Mapping Using One Wheel-mounted IMU
Yibin Wu, Jian Kuang, Xiaoji Niu +3
A reliable pose estimator robust to environmental disturbances is desirable for mobile robots. To this end, inertial measurement units (IMUs) play an important role because they ca…
DynaVIG: Monocular Vision/INS/GNSS Integrated Navigation and Object Tracking for AGV in Dynamic Scenes
Ronghe Jin, Yan Wang, Zhi Gao +3
Visual-Inertial Odometry (VIO) usually suffers from drifting over long-time runs, the accuracy is easily affected by dynamic objects. We propose DynaVIG, a navigation and object tr…
IC-GVINS: A Robust, Real-time, INS-Centric GNSS-Visual-Inertial Navigation System for Wheeled Robot
Hailiang Tang, Tisheng Zhang, Xiaoji Niu +2
In this letter, we present a robust, real-time, inertial navigation system (INS)-Centric GNSS-Visual-Inertial navigation system (IC-GVINS) for wheeled robot, in which the precise I…
OdoNet: Untethered Speed Aiding for Vehicle Navigation Without Hardware Wheeled Odometer
Hailiang Tang, Xiaoji Niu, Tisheng Zhang +2
Odometer has been proven to significantly improve the accuracy of the Global Navigation Satellite System / Inertial Navigation System (GNSS/INS) integrated vehicle navigation in GN…
Exploring the Accuracy Potential of IMU Preintegration in Factor Graph Optimization
Hailiang Tang, Xiaoji Niu, Tisheng Zhang +2
Inertial measurement unit (IMU) preintegration is widely used in factor graph optimization (FGO); e.g., in visual-inertial navigation system and global navigation satellite system/…
Wheel-INS2: Multiple MEMS IMU-based Dead Reckoning System for Wheeled Robots with Evaluation of Different IMU Configurations
Yibin Wu, Jian Kuang, Xiaoji Niu
A reliable self-contained navigation system is essential for autonomous vehicles. Based on our previous study on Wheel-INS \cite{niu2019}, a wheel-mounted inertial measurement unit…
A Comparison of Three Measurement Models for the Wheel-mounted MEMS IMU-based Dead Reckoning System
Yibin Wu, Xiaoji Niu, Jian Kuang
A self-contained autonomous dead reckoning (DR) system is desired to complement the Global Navigation Satellite System (GNSS) for land vehicles, for which odometer-aided inertial n…
Inertial Sensing Meets Artificial Intelligence: Opportunity or Challenge?
You Li, Ruizhi Chen, Xiaoji Niu +4
The inertial navigation system (INS) has been widely used to provide self-contained and continuous motion estimation in intelligent transportation systems. Recently, the emergence…
Autonomous Calibration of MEMS Gyros in Consumer Portable Devices
You Li, Jacques Georgy, Xiaoji Niu +2
This paper presents a real-time calibration method for gyro sensors in consumer portable devices. The calibration happens automatically without the need for external equipment or u…
Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation
You Li, Yuan Zhuang, Xin Hu +12
The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to…
Wheel-INS: A Wheel-mounted MEMS IMU-based Dead Reckoning System
Xiaoji Niu, Yibin Wu, Jian Kuang
To improve the accuracy and robustness of the inertial navigation systems (INS) for wheeled robots without adding additional component cost, we propose Wheel-INS, a complete dead r…