Digital Twinning is creating an electronic or a virtual version of a real-world thing and keeping them in sync in real-time.
That applies to more than just robotics.
An example of a digital twin could be seen in self-driving cars.
Self-driving cars can benefit from having a digital twin (virtual simulation) of the environment they're in, but you can also have a digital twin of the car itself.
It's also very dangerous to put a self-driving car you're working on in the streets. Using digital twins, you're able to develop the AI for the self-driving car in a safe environment that's as real to the outside world as possible.
When the car is on the real road, there are real consequences if something goes wrong.
Digital twins help solve this issue by creating a virtual simulation of the car's environment and the car itself.
When you put the two together, you can safely try new algorithms, use machine learning, which learns by making mistakes. Everything happens in a virtual environment, so if something goes wrong. You don't have to worry about wrecking your car or harming people.
Potential Problems With Using Digital Twins
If you're not bringing in experts on digital twins, you could quickly run into problems once you develop your AI in the real world.
If the gravity, collision, size, or any other physics / physical feature is in your simulation, your robot will not function as intended.
Let's say you're using Unity to create an environment. It would be best if you made an accurate environment, especially the sensors on your robot.
If the robot sensors are off, it's not going to behave exactly the same in the real world as it did in the virtual environment.
Your environment needs to match what you see very accurately.
If you've ever played video games, you've undoubtedly run into "invisible walls."
An invisible wall is a boundary in a video game that limits where a player character can go in a particular area but does not appear as a physical obstacle.
Invisible walls shouldn't happen in a digital twin. If there aren't any physical obstacles, the robot needs to access the location, especially if you're training your robot to use LIDAR.
LIDAR is a sensor that the robot can use to take distance measurements, they're very accurate distance measurements, and that's a big way how robots navigate in the environment.
Summary: If you're an expert on digital twins, we advise that you hire experts like us to help make your digital twin a success. Otherwise, you might spend a lot of time and money developing virtual environments that don't work in the real world.
Do You Need A "Supercomputer" To Use Digital Twinning?
Having a strong computer will undoubtedly help you simulate as many tests as you want and increase your machine learning efforts' speed.
However, you don't need to own one of these supercomputers, and neither does your staff.
You can easily rent out a strong cloud machine from companies like Google and AWS to run your virtual environment.
Or if you already have a robust machine, but your employees don't, you can give your employees access to the machine via the cloud.
How Do You Use Digital Twinning In Robotics?
You can use digital twins for a wide range of purposes, including
machine learning, diagnostics, and algorithm testing.
Using digital twins also allows companies to experiment in a low-risk environment.
You don't have to spend money on procurement, materials, and production, and you know much sooner if you need to make changes before moving forward.
Most of the time, you want to add robots to your warehouse, and you don't know-how. This is where digital twins come in.
With the almost unlimited scale in a low-risk environment, you can find the perfect solution for your warehouse.
The goal is to create the perfect robots before investing millions of dollars assembling them in your warehouse. Also, since tests are being done in a digital environment, you don't need to stop your workers from doing their job or building a separate warehouse for testing.
You have it all in the digital world.
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