12 papers
Distributional Soft Bellman Operator under the Cramér Geometry
Keru Wang, Yixin Deng, Yao Lyu +2
Distributional soft policy iteration (DSPI) provides an important framework for combining distributional reinforcement learning (DRL) with maximum-entropy control, in which the pol…
M3imic: Learning a Versatile Whole-Body Controller for Multimodal Motion Mimicking
Zuxing Lu, Ziang Zheng, Yao Lyu +7
Building a general-purpose whole-body controller is essential for enabling diverse motion capabilities in humanoid robots across a wide range of downstream tasks, including locomot…
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…
Natural Gradient Bayesian Filtering: Geometry-Aware Filter for Dynamical Systems
Chang Liu, Wenhan Cao, Zeju Sun +8
Bayesian filtering is a cornerstone of state estimation in complex systems such as aerospace systems, yet exact solutions are available only for linear Gaussian models. In practice…
Augmented Lagrangian Multiplier Network for State-wise Safety in Reinforcement Learning
Jiaming Zhang, Yujie Yang, Yao Lyu +2
Safety is a primary challenge in real-world reinforcement learning (RL). Formulating safety requirements as state-wise constraints has become a prominent paradigm. Handling state-w…
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…