Lihui Wang
Southeast University
30 Papers
91 Citations
Lihui Wang is an academic researcher from Southeast University. The author has contributed to research in topics: Inertial navigation system & Computer science. The author has an hindex of 8, co-authored 17 publications. Previous affiliations of Lihui Wang include Chinese Academy of Sciences & Chinese Ministry of Education.
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Papers
A digital twin-based sim-to-real transfer for deep reinforcement learning-enabled industrial robot grasping
Yongkui Liu,He Xu,Ding-Chung Liu,Lihui Wang +3 more
- 01 Dec 2022
TL;DR: In this paper , a digital twin-enabled approach for achieving effective transfer of DRL algorithms to a physical robot is proposed, where the output of the digital twin system is used to correct the real grasping point so that accurate grasping can be achieved.
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A fast compass alignment method for SINS based on saved data and repeated navigation solution
TL;DR: A fast compass alignment method based on iterative calculation is designed for Strapdown INS and the simulation result shows that the forward–forward navigation solution method is more effective for compass alignment than the backward–forward one.
40
A novel self-alignment method for SINS based on three vectors of gravitational apparent motion in inertial frame
Xixiang Liu,Xixiang Liu,Xianjun Liu,Xianjun Liu,Qing Song,Qing Song,Yan Yang,Yan Yang,Yiting Liu,Yiting Liu,Lihui Wang,Lihui Wang +11 more
TL;DR: Based on the alignment idea of tracing gravitational apparent motion in inertial frame, a novel self-alignment and latitude calculation method for Strapdown Inertial Navigation System (SINS) is designed as mentioned in this paper.
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An innovative PSO-ICCP matching algorithm for geomagnetic navigation
TL;DR: In this paper , an innovative PSO-ICCP geomagnetic matching algorithm is proposed to eliminate the cumulative error in inertial navigation system (INS), where PSO and ICCP are combined to diminish the sensitivity of ICCP to initial error with the global search capability of PSO.
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A Method for SINS Alignment with Large Initial Misalignment Angles Based on Kalman Filter with Parameters Resetting
TL;DR: In this paper, the authors investigated the problem of large misalignment angles in SINS initial alignment, and the key reason for alignment failure is given as the state covariance from Kalman filter cannot represent the true one during the steady filtering process.