Technology

Should you Take an Industrial Robotics Class?

As I sit and write this, I have just completed an eight week course on how to operate industrial robots. Yes, those industrial robots. The big robot arms that you see in Tesla’s German factories that allow Elon Musk to produce vehicles at an outstanding speed at a hyper-efficient cost.

Honestly, I was shocked by how fun and interesting the course actually was. I haven’t been so surprised since I checked out Sloto Cash. How many of my classes can I actually say that about, especially for classes that were mandatory? So why did I do it, what have I learned, and is it worth it for you?

Why did I take Industrial Robotics?

So a little bit about me. I’m an engineering student. I have just completed my second year. I am studying mechatronics as part of the military program where the army pays a majority of the bill, in exchange for extended service time.

In my specific track, I double in both an engineering degree and a practical engineering certificate (which is what I’m about the be earning soon). As part of this latter certificate, I got to take a bunch of practical classes that I otherwise wouldn’t have. Case in point: Industrial Robotics.

What is Industrial Robotics?

Specifically, it’s the kind of robots that are used for mass production. Like the example above, in Elon Musk’s Tesla factories. However, the advantage of these kinds of robot arms is that they are super versatile. They are basically giant arms with 100% customizable hands.

Throughout the course I saw examples of these robots being used in all sorts of professions, from welding to packaging cookies. This class teaches the basics behind operating such a robot, and how to prepare one to operate based on the various needs of whatever company you’re working for.

How does it work?

The robots themselves are very complex and ingenious machines. They can range from small enough to sit on a desk (like the ones I was allowed to play with) to massive ones capable of lifting cars. Although a lot of these robots look similar on the outside, they can vary wildly on the inside. The ones I was taught use motors, gears, and rubber belts for a useful, but still limited, 5 axii of motion. Industrial ones can have seven or more with G-d-knows-what inside.

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By design, operating these robots are fairly simply. I was taught to use a software called “Robocell”, and it’s very simple once you get your head around it. Within the software you can set up a simulation of the environment you want the robot to work in.

Then, you can pick from a long list of commands what you want the robot to do. When told, the robot will run through each command one by one until it reaches the end of the program. And aside from the nuances and syntax of the commands themselves, that’s basically it.

However, there are some important things to keep in mind while working. These robots are big, dumb, and blind. While the little ones I was allowed to play around with neither move fast nor are particularly strong, you can bet industry-tier versions absolutely are.

These machines will do exactly what you tell them to do, and it doesn’t matter if what’s between its grippers is a sheet of metal or a person’s head. So be careful.

That’s not to say that all these machines are dangerous. There are ones meant to work safely beside humans. Cobots, a cute name for Collaborative Robots, have multiple cameras, screens, and sensors- and lack strength. This makes these robots perfect for very sophisticated tasks that don’t require a lot of exertion.

The generally safe nature of Cobots makes them ideal for implementation in a workplace that still requires humans to move around in, such as factory lines or hospitals. Cobots also has another advantage in that they are easily reprogrammable, compared to industrial machines that require CAD/CAM based simulation tools… such as RoboCell.

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Was my time well spent?

Robots are the future. It’s not a question. They are already here, and they are here to stay. There are two things that limit their applicability: Their physical bodies and their limited brains.

Robots need to be specially designed for the specific task they are intended to do. A Roomba is never going to replace a garbage man, or fix your plumbing. More generalized robots are in the works, of course, but they are far from ready. You can look into Google’s research team, “Everyday Robots” for some of the leading tech in this area.

However, more specialized robots are already in operation, and are already replacing jobs. Take self-driving cars. They’re already on the road, and companies like Mobileye have fleets of these machines being trained in Jerusalem, Munich, Detroit, Tokyo, and Paris. Transport is the number one job industry in the world, and robots are gunning for those jobs.

The second half of robots is the brain. Again, we’re very far along with software being capable of solving very complex problems. These programs are called “Neural-Networks”. They are very much based on how our own brains work, and use nodes and weights and a lot of matrix math to solve very intricate problems, like understanding language and avoiding running over children in the street.

These robots don’t have to be perfect at what they do either. They just have to be better than us, and a lot of them already are.

So yeah, I think it was worth learning about these things. The industry is going to move more and more towards robots as quickly as it can, because robots will work 24/7 without complaint for a fraction of the cost of human labor.

Where does that leave everyone else?

There are a lot of jobs that are in trouble because of robotics, and not just manual labor ones either. These neural networks are reducing the need for humans in tons of fields. Even doctors and lawyers are seeing aspects of their jobs automated.

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Some of these Neural nets can detect tumors in scans that even radiologists miss, and a lot of the paperwork legalize can be handed off to a bot that can read through thousands of documents in seconds. Artists are going to see the scope of their profession shrink, as software like Dall-E can create astounding images that can be used for prototyping and concept art.

So the jobs that are going to remain are going to have to either require a) multiple physical demands that require dexterity. Ain’t no robot plumber that’s gonna fix the pipes under your sink anytime soon. b) novel problem-solving. Robots are very good at handling things they are trained for, but ask these robots to step outside of their realm of understanding and they fail quickly. A language-model neural net has a hard time understanding jokes and sarcasm, and certainly doesn’t actually understand the things it talks about, like love. It just knows what the likely response of someone who claims to be in love would be. c) actual desire. Robots have yet to show any desire to do anything for themselves, and that whole debacle with Google’s Lambda was because the software was asked leading questions. Robots don’t do anything when they aren’t being used.

So… the short answer is to try and transition to jobs with better security. There are lot of trades that are in no risk of being replaced, simply because of how difficult to simulate the body motions required to do them. We humans are extremely adaptable, and can change if we need to. But it’s gonna hurt bad for those that don’t see where the wind is blowing, refuse to see, or refuse to budge. And that will hurt everyone, directly or no.

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