44 citations · 53 across the 8 of their papers we have counts for
8 papers
Interacting Multiple Model Proprioceptive Odometry for Legged Robots
Wanlei Li, Zichang Chen, Shilei Li +2
State estimation for legged robots remains challenging because legged odometry generally suffers from limited observability and therefore depends critically on measurement constrai…
Lie-algebra Adaptive Tracking Control for Rigid Body Dynamics
Jiawei Tang, Shilei Li, Ling Shi
Adaptive tracking control for rigid body dynamics is of critical importance in control and robotics, particularly for addressing uncertainties or variations in system model paramet…
Secure State Estimation of Cyber-Physical Systems via Gaussian Bernoulli Mixture Model
Xingzhou Chen, Nachuan Yang, Peihu Duan +2
The implementation of cyber-physical systems in real-world applications is challenged by safety requirements in the presence of sensor threats. Most cyber-physical systems, especia…
Bias-VarianceTrade-off in Kalman Filter-Based Disturbance Observers
Shilei Li, Dawei Shi, Xiaoxu Lyu +2
The performance of disturbance observers is strongly influenced by the level of prior knowledge about the disturbance model. The simultaneous input and state estimation (SISE) algo…
On the Effects of Modeling Errors on Distributed Continuous-time Filtering
Xiaoxu Lyu, Shilei Li, Dawei Shi +1
This paper offers a comprehensive performance analysis of the distributed continuous-time filtering in the presence of modeling errors. First, we introduce two performance indices,…
Generalized Multi-kernel Maximum Correntropy Kalman Filter for Disturbance Estimation
Shilei Li, Dawei Shi, Yunjiang Lou +2
Disturbance observers have been attracting continuing research efforts and are widely used in many applications. Among them, the Kalman filter-based disturbance observer is an attr…
Multi-kernel Correntropy Regression: Robustness, Optimality, and Application on Magnetometer Calibration
Shilei Li, Yunjiang Lou, Dawei Shi +2
This paper investigates the robustness and optimality of the multi-kernel correntropy (MKC) on linear regression. We first derive an upper error bound for a scalar regression probl…
Multi-kernel Correntropy-based Orientation Estimation of IMUs: Gradient Descent Methods
Shilei Li, Lijing Li, Dawei Shi +2
This paper presents two computationally efficient algorithms for the orientation estimation of inertial measurement units (IMUs): the correntropy-based gradient descent (CGD) and t…