Reinforcement Learning-Based Control for Smooth and Accurate Circular Trajectory Tracking in Mobile Robots
This paper investigates reinforcement learning-based control for smooth and accurate trajectory tracking of a nonholonomic mobile robot. Three reinforcement learning algorithms, Deep Q-Network (DQN), Proximal Policy Optimization (PPO), and Soft Actor-Critic (SAC), are implemented and evaluated, with conventional PID an...