How does AI interact with robotics?
Artificial intelligence and machine learning involves software programs classifying data and making decisions about things in the real world. Robotics involves manipulating objects in the real world. This creates the ability to manipulate the real world using a combination of machine learning and robotics.
At the same time, artificial intelligence programs can use data from the real world acquired through robotics to improve their performance. AI/machine learning have a symbiotic relationship.
One obvious application of AI to robotics is in computer vision. Computer vision allows robots and drones to navigate the real world more accurately. This has other applications for people: One experimental robot could remind people about ordinary things such as leaving milk outside of the refrigerator.
Robots are already used in manufacturing, but usually in preprogrammed tasks. Robots could learn tasks with machine learning by being shown by humans or through unsupervised machine learning. That means they could be moved to new jobs without a person having to reprogram them.
While there is concern that robots like these could replace people in manufacturing jobs, these robots could work alongside humans as “cobots,” where they collaborate with people instead of taking over their jobs.
Another major application of AI to robotics that has gotten attention in recent years is autonomous or self-driving cars. This kind of application is attractive because human driver error is the most common cause of accidents. A robotic car won’t get tired, impaired, or inattentive the way a human driver can. While there have been a few high-profile accidents involving autonomous vehicles, they have a lot of potential to be safer than human-driven vehicles.
A major research area involving robots and AI is in medical technologies. Robots in the future could perform surgery without intervention from a human doctor. As with autonomous vehicles, robotic surgeons could perform delicate operations for longer than human doctors can, without getting tired or making mistakes.
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- Artificial Intelligence
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- Unmanned Aerial Vehicle
- Unsupervised Learning
- Collaborative Robot
- Autonomous Vehicle
- Natural Language Processing
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