These Are the Top 5 Applications of Artificial Intelligence in Robots
At the ARM Institute, we spend a lot of time talking about the hardware we often associate most with robots. This is a natural subject for an organization focused on manufacturing and our role in connecting job seekers to careers in robotics. But robots are more than just the hardware, they’re also software. While many robots in manufacturing and other industries are programmed to very precise specifications, artificial intelligence (AI) has a bigger role than ever.
Vision and Imaging
A robot that continuously makes the same motion over and over again is common in manufacturing, but the flexibility of artificial intelligence allows for even more capabilities. Artificial intelligence can be used to improve a robot’s visual acuity and the accuracy of its image recognition. These are important for assembly, as robots welding or cutting can adapt to the smallest micro-level tolerances. Accurate vision is also important to logistics, as a robot with high visual acuity can put the right objects in the right containers no matter what those objects or containers are.
Grasping and Manipulation
Artificial intelligence is about more than just enabling independent action–a robot in manufacturing can actually develop better ways to mechanically interact with the world. A robot using artificial intelligence in developing the best, most efficient ways to utilize its moving parts. Like most applications of AI in robotics, the bulk of work done in this area is done long before the robot is operating on the factory floor and is a part of an overall machine learning phase.
Machine Learning Applications
If you have a robotic vacuum in your home, you’ve already seen a smaller, less advanced version of the methods used to train robots in manufacturing. A robot explores its surroundings, learning more about where it is, what obstacles it will need to navigate, and what challenges it will need to overcome in order to accomplish the tasks important to its primary purpose. For a vacuum cleaner, this data is usually no more complicated than a path to travel or, occasionally, what strength of suction is needed depending on the surface.
Once a robot learns where it can go and what it needs to do, those computing cycles can be focused on accomplishing its tasks rather than learning how to do them. There is always the option of pre-programming in those situations where learning might not be the best approach.
Another kind of artificial intelligence that many people have encountered in their daily lives is the customer service artificial intelligence implementation known as a chatbot. These are the automated service agents on websites that can help with simple, frequent, repeatable requests that don’t require a human agent. Customers often have questions like “did my package ship yet?” or “what are your hours?” that are easy for AI to parse, and can be answered with much the same simplicity.
While a chatbot is not a robot in the traditional sense, the same kind of questions are frequently asked at brick and mortar stores that take the valuable time of human beings who are better used elsewhere. If a robot can be programmed to patrol a physical location, answering questions, helping customers, the savings will add up.
The other side of the customer service coin is employee service. These are often also called cobots, as they cooperate with human users, such as assembling and then handing off a component to a human inspector. Since a cobot’s operations are flexible and less rigidly defined than other robots in manufacturing, more and more they are relying on AI to do more sophisticated tasks. The nature of cobots allows for them to be used in many ways and for many purposes, from answering questions to providing remote telepresence to management or off-site employees.
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