With the advancement in technology, the robotics is no more a field of research in artificial intelligence. It has now transformed into a field where you can include all aspects of AI.
We can take an example of hospitals in the U.S where healthcare robots are being used as a delivery robot to carry medicines and supplies. All you need to do is call the robot by his name, and he’ll respond within seconds, and you can ask him for any work, and he’ll do it for you.
We’ve seen a tremendous growth of artificial intelligence in the last few years, and this growth has led to an increase in adoption of robotics, automation and artificial intelligence. If we talk about a recent big survey which was held in 2018, around 41 per cent of people consider AI in robotics. Among the rest, 47 per cent of them is looking forward to doing something in automation or AI.
With the growing industry and the increasing adoption, it’s right to say that it’s worth paying attention to robotics. As we had last year, a robot, named Sophia, walks, talks, move from one place to another, just like humans. The focus is to take robotics and AI to the next level and to make them more like human so that they can help us in our daily affairs. It has all become possible because of the experts and investors who had been believing in AI that it will grow to the next level and today we’re getting closer to the next big thing.
We’ve seen Sophia the Robot, that experts have tried their best to work on its sensors just like we have a sensory system, they’ve been attempting to build the same so that it can be more like a human. To know AI in robotics, one should know what the building blocks are.
So to make you understand all about AI in robotics, we’ll explain the types of sensors used in robotics.
Types of Sensors
Sonar Sensors: These sensors are not being used now because they’re dependent on the reflection of a reflective surface. In simple terms, we can say that they emit sensor rays on the opposite way to the sensor. The distance between the sensor and the apparent item is the time between the emanation of sound and its bounce back from the visible deterrent.
Infrared Sensors: These sensors work inside the scope of 80 cm. The sensors emanate the rays to the other way to the sensor and get a bounce back from a repository. The total distance between the sensor and obstacle is the time between rays transmission and reception.
Laser Sensors: These are the third type of sensors which can work inside the scope of 180-degree. They depend on the type of laser being used. Their use in robotics marks efficiency.
Now, below are the two essential points which are essential for tech junkies if they want to know AI in a better way.
Automation is in the air
To make you understand about the use of AI in robotics in a better way, let’s take an example of the retail industry. Albertsons, being one of the leading grocery retailers, has planned for a customer hassle free order picking via robots. Isn’t it something new and unique?
When you order something, and a delivery executive comes down to deliver, how much time does it take? A lot of time. So to fasten the whole process, the company looks forward to making robots deliver your order. This is not unique, but it will also eliminate the time taken to pick items and get them delivered.
We can take another example of JD.com; A Chinese online retailer has partnered with Japanese AI startup Mujin. Here they are following what we’ve discussed above. Yes, you heard it right. Here robots will not only pick up your order but will also pack them up.
Secure future actions
Have you ever thought of this that what if computers could learn?
Man has created a computer for solving problems, to make lives easy. So they’re the problem solvers but in limited fields. The idea of AI is simple, but the implementation is not. Computers can then collect facts about any situation through sensors, and then they compare the info with the data which was stored earlier, and then they give results. They are unable to learn things. They deliver results based on data stored in them.
Every action of the computer relies upon its programming as it lacks in learning.
AI-based robots come up with limited capacity due to their deep neural network. Apart from automation, learning robots are capable of evaluating actions and provide you with business related insights.
Artificial intelligence based robots think of constrained limit because of their profound neural system. Apart from it, if you want business related insights, then learning robots can be used as they are capable of evaluating actions and giving insights.
That was about how computers take actions and where they lack. But if we talk about robots, they outpace computers to some extent. Robots can store information and take action when the same scenario occurs.
Today, many countries are working AI and robots; Japan owns a robot that can not only walk and talk like humans but can also dance by anticipating the moves of the body.
There’s another example of a robot at M.I.T’s Artificial Intelligence Lab, Kismet. This robot can analyse and evaluate human body language and voice inflexion.
The idea is not just to make robots do our work but to lay a foundation of a system which can learn things like humans through visuals and voice.
Arsene Wenger had predicted robots that they’d soon work as the managers.
He also said that with the help of social media polls, it would be decided that whether this robot should get this job or not.
We know that there’s still a lot to cover in the world of AI, and we know it all that one day, it will be transforming lives. Today we are making decisions based on robotic insights. Now we need to learn about big data and to leverage it.
Hopefully, in the coming years, we are likely to face innovations in AI.
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