Today's robots excel in highly constrained environments like factories, performing specific tasks with precision. However, they struggle in unconstrained settings, such as homes, where unexpected events require adaptability. The current limitations stem from pre-programmed movements, making it challenging for robots to react dynamically. As a result, advancements in machine learning are essential to enhance robotic capabilities in more varied environments.
