M. Tabash

Hybrid Computed Torque Control and Soft Actor-Critic Framework for Sample-Efficient Robotic Manipulator Control

Reinforcement Learning (RL) has emerged as a promising approach for robotic control, enabling agents to learn control policies through interaction with complex and dynamic environments. However, standalone RL methods often suffer from poor sample efficiency, limiting their practicality for real-world robotic systems. T...