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