Part 3/11:
Historically, robotic systems have been characterized as specialist machines, crafted to excel at a single function. Think of robotic vacuums that clean floors, industrial arms that assemble cars, or sortation robots on conveyor belts. While effective within narrow scopes, these machines suffer from a critical drawback: poor adaptability. They cannot easily learn new tasks without extensive reprogramming or hardware modifications, limiting their broader utility.
This rigidity stems from their reliance on pre-defined programming tailored for specific tasks, making them ill-equipped to handle unpredictable or varied environments. As a result, they often require humans to supervise or intervene, especially when navigating unfamiliar settings.