12 papers
FUSE: A Framework for Unified State Estimation in Vehicular and Robotic SLAM Systems
Wei Wu, Honglin Chen, Wenhan Cao +7
Tightly coupled SLAM formulations under mixed-rate sensing often bind temporal processing, local geometric association, estimator formulation, and map-update policy into method-spe…
On the Optimization Landscape of Observer-based Dynamic Linear Quadratic Control
Jingliang Duan, Jie Li, Yinsong Ma +5
Understanding the optimization landscape of linear quadratic regulation (LQR) problems is fundamental to the design of efficient reinforcement learning solutions. Recent work has m…
Natural Gradient Gaussian Approximation Filter on Lie Groups for Robot State Estimation
Tianyi Zhang, Wenhan Cao, Chang Liu +2
Accurate state estimation for robotic systems evolving on Lie group manifolds, such as legged robots, is a prerequisite for achieving agile control. However, this task is challenge…
Natural Gradient Gaussian Approximation Filter with Positive Definiteness Guarantee
Tianyi Zhang, Wenhan Cao, Shengbo Eben Li
Popular Bayes filters often apply linearization techniques, such as Taylor expansion or stochastic linear regression, to enable the use of the Kalman filter structure, but this can…
Nonlinear Bayesian Filtering with Natural Gradient Gaussian Approximation
Wenhan Cao, Tianyi Zhang, Zeju Sun +3
Practical Bayes filters often assume the state distribution of each time step to be Gaussian for computational tractability, resulting in the so-called Gaussian filters. When facin…
One Filters All: A Generalist Filter for State Estimation
Shiqi Liu, Wenhan Cao, Chang Liu +3
Estimating hidden states in dynamical systems, also known as optimal filtering, is a long-standing problem in various fields of science and engineering. In this paper, we introduce…