https://www.youtube.com/watch?v=mQqm_vFo7e4 Actor-Critic Model Predictive Control Angel Romero, Yunlong Song, Davide Scaramuzza The authors are with the Robotics and Perception Group, Department of Informatics, University of Zurich, and Department of Neuroinformatics, University of Zurich and ETH...
Model predictive control (MPC)Soft actor-critic (SAC) algorithmPath planningPath trackingDual actor networksIn this paper, a framework of active obstacle ... Y Chen,S Wu - 《Journal of Transportation Engineering Part A Systems》 被引量: 0发表: 2023年 Discretionary Lane-Change Decision and Cont...
In this reinforcement learning tutorial, we will demonstrate how to use a soft actor-critic agent to solve control tasks for complex dynamic systems such as a redundant robot manipulator. The goal of the task is to design a model-free controller with a soft actor-critic agent ...
employed in general APS include quintic polynomial curve, cubic spline curve, cyclotron curve, and hybrid A-star algorithm, for tracking control, the commonly used algorithms are proportion-integral-derivative (PID), linear quadratic regulator (LQR), and model predictive control (MPC) [10]–[14]...
-1- 中国科技论文在线 自适应重要采样 Actor-Critic算法 冯涣婷 中国矿业大学信息与电气工程学院,江苏徐州(221116) 摘 要:在离策略 Actor-Critic(AC)强化学习中,虽然 Critic使用重要采样技术可以减小值函 数估计的偏差,但是重要采样方法没有考虑估计的方差,算法性能倾向于不稳定。为了减小 估计方差,提出一种自适应...
Use neural networks to model both the parametrized policy within the actor and the Q-value function within the critic. For this example, use the helper functions createLaneKeepingCritic and createLaneKeepingActor to create the critic and the actor, along with their training options sets. Get...
In [24], soft actor–critic RL is used to fast charge a Li-ion battery cell using an electro-thermal model. However, the study in [24] lacks an aging model and does not consider the impact of a cooling system. The work in [25] employs RL to train a neural network for fast chargi...
As mentioned before, we propose a continuous control optimization for moving target tracking based on soft actor-critic. In this section, we will discuss simulation results of the moving target tracking model. A total of 10000 iterations training were performed using a computer with a NVIDIA GeForc...
The goal of the task is to design a model-free controller with a soft actor-critic agent that can balance a ping-pong ball on a flat surface attached to the end effector of the manipulator. Model-based control techniques like Model Predictive Control (MPC) or other methods ...
In engineering, a hexapod robot foot trajectory tracking control method based on Udwadia–Kalaba theory was proposed, which had a faster error convergence and response speed compared with the traditional sliding mode space [27]. An omnidirectional tracking strategy based on model predictive control and...