4 papers
Distributional Soft Actor-Critic with Diffusion Policy
Tong Liu, Yinuo Wang, Xujie Song +6
Reinforcement learning has been proven to be highly effective in handling complex control tasks. Traditional methods typically use unimodal distributions, such as Gaussian distribu…
Distributional Soft Actor-Critic with Harmonic Gradient for Safe and Efficient Autonomous Driving in Multi-lane Scenarios
Feihong Zhang, Guojian Zhan, Bin Shuai +3
Reinforcement learning (RL), known for its self-evolution capability, offers a promising approach to training high-level autonomous driving systems. However, handling constraints r…
Design and Experimental Test of Datatic Approximate Optimal Filter in Nonlinear Dynamic Systems
Weixian He, Zeyu He, Wenhan Cao +5
Filtering is crucial in engineering fields, providing vital state estimation for control systems. However, the nonlinear nature of complex systems and the presence of non-Gaussian…
Transferable Latent-to-Latent Locomotion Policy for Efficient and Versatile Motion Control of Diverse Legged Robots
Ziang Zheng, Guojian Zhan, Bin Shuai +4
Reinforcement learning (RL) has demonstrated remarkable capability in acquiring robot skills, but learning each new skill still requires substantial data collection for training. T…