Deep learning has emerged as a powerful paradigm in robotics, enabling robots to achieve advanced control tasks. Deep learning for robotic control (DLRC) leverages deep neural networks to learn intricate relationships between sensor inputs and actuator outputs. This methodology offers several advantages over traditional control techniques, such as