[brutus1979]

I'm really intrigued by robotics as future career. How would you rate it for the next 10-15 years? I'm seriously thinking of investing in a masters degree focused on robotics (CMU). I'm close to 50 and already have a cs PhD. Just intrigued by it and feel it might have a longer career (when it takes off).

[sashank_1509]

Wow, you’re still interested in learning at close to 50. That’s commendable. I did my masters at CMU robotics, and I would recommend doing it. Most students will be under 30, but CMU is a very practical school with an actual focus on building and programming robots, so if you’re proactive you can wet your feet plenty during your masters programme. Don’t expect to learn much from courses though, most of the learning happens in your off time in robotics projects or when doing robotics research with professors, and in that CMU is really good

[jvanderbot]

I'll try not be insulted by this. I'm 40+ and pivot myself nearly every year.

I think a lot of the "I don't see >40y/o swe" is a combo of:

There were more CS/IT grads from 2000 to today (<40 years old) than were ever produced prior to year 2000.

After 40 you tend to move into management, consulting, or just switch careers, b/c SWE pays well.

After 40 you don't work at companies that churn through young devs (so young devs are less likely to work with > 40 y/o)

[liendolucas]

Robotics is a very hard topic. If on top of that you add ROS which almost everyone is using you will end up very disappointed and without much enthusiasm to do robotics at all. My major criticism to ROS is that because robotics is already hard, ROS does not make it a single bit enjoyable or easy, all the opposite as a matter of fact.

[Joel_Mckay]

Built a few platforms over the years, and can concur robotics is nontrivial.

ROS has some fundamental design flaws, but does integrate most development software from various research areas. In many cases, the sub-projects were abandoned decades ago, and only ROS developers keep these components operational.

The primary mistake most naive academics make is assuming you are dealing with a single problem domain. Robotics is different from simple automation in that it has 4+ different primary concurrent systems that must share state.

There is also the IP issues with parts of projects like OpenCV, and the patent holders (university legal departments) make it nearly impossible to license. i.e. unless you have >$3m to drop on each component... expect to get ignored or sued in a commercial setting.

This is why we can't have nice things, as most FOSS software is perpetually Beta ... Thus, nearly impossible to "clean" and deploy in a commercial setting due to coincidental contamination from the original IP rights holders (not the coder.) =3

https://youtu.be/_lOT2p_FCvA?si=10TqsftmOedHPG-B&t=30

[f1shy]

You have a CS PhD? I highly doubt you can learn something there. If it is about knowledge, find out what books are used in the masters. With a PhD you must be able to learn yourself

[ModernMech]

Robotics is very different from CS. At CMU robotics is huge and consists of thousands of researchers, with dozens of classes a MS student would have never encountered during their CS PhD or undergrad. It's true you can learn robotics from books, but CMU or any grad program has access to robotics hardware resources you can't find online or in the library. For example I took a course there that had the Aldebaran Nao as a platform. The course has a dozen of them, at the time they were worth $20k a piece.

[f1shy]

About the theory, you can learn yourself (I think) about practice, well, you may learn 1 or 2 platforms, but not all. If you get a job, you will for sure have to learn a lot from the platform they use, but much more of the application they do. Also the platforms get obsolete fast…

What about buy 2nd hand/use/resell some hardware? I do not know how much cost a Ms in CMU, but sure does bot even compare to 20k.

Sorry maybe I’m a little bit negative, but if you have already one good title, that is more than enough. The problem is I fully subscribe to Stallone[0]

[0] https://m.youtube.com/shorts/srEsT5h4gdo

[ModernMech]

That’s $20k for one robot. If you want exposure to the breadth of hardware a ME at CMU would bring, you’d need access to the facilities as well. Robotics takes space most people don’t have.

[f1shy]

But Ms at CMU, aren’t you looking at about 400k?!

[corysama]

Robotics is already taking off. It’s just not evenly distributed. I think several companies are being highly optimistic in their projections of millions of humanoid robots in five years. But, I think it’s the common mistake of overestimating the short term and underestimating the long term.

[mitthrowaway2]

FWIW, I hear that CMU is a very good school for robotics.

[jvanderbot]

Now is an excellent time to work in robotics. Every major car company will be transitioning their car offerings to semi-robotic systems. Every major Army, navy, or air force will be adopting automated systems in an increasing degree. Decent wages for bluecollar work means decent prices for automated systems. The buildout of American manufacturing means automation is key. Finally, space exploration booms mean robots (not necessarily fully autonomous, but largely automated systems) are in increasing demand for aerospace too. Is spaceX building robots? Yes they are!

I would recommend the masters for the coursework and practical background. A degree from CMU will get you through the pedigree filter at most jobs. I've hired plenty of CMU masters students and have always been happy with them.

Robotics itself does have many of the job archetypes you'd expect from a hardware/software heavy industry.

Regardless of the path, specialization is key. You might be (woefully incompletely) categorized as:

- systems folks (middleware, CUDA, distributed systems, hard C, C++, ROS-like, etc). Even things like CI/CD knowledge as applied to robotics can get you a long way.

- Vision (CNN/DL, but do not stop there. You should also have basic knowledge of tracking, homographies, and the old school CV stuff to make it work well in a system (as opposed to just scoring high on training data))

- Controls (PID and the bigger cousins - this is not my area)

- Tracking (EKF and the bigger cousins - in particular MH-EKF and please don't skimp on batch filters we have enough CPU to do that nowadays)

- Mapping & Prediction (often this is done so poorly that a person who has lots of practice building 2d/3d and semantic maps is a godsend, especially incorporating uncertainty - critically predicting future maps (+5-30s) is an amazing thing to have)

- Planning (99% of planning nowadays is trajectory planning which is kind of "just" figuring out from a map and destination what the signal is over time that goes to the control subsystem. But there's also route planning- where should we go an in what order, activity planning (what are good destinations and in what order), or even multi-agent planning (how do I get a bunch of agents to not just collide when trying to do individual activities))

- Proprioception (Sometimes just called Estimation) you'll want to be an expert in IMUs, Gyros, the EKF filter, using vision signals, magnetic signals, GPS, etc

- Exterioception (more general than Tracking) options are LIDAR, Radar, Bog-Standard Dispartiy, or any other sensor you can think of.

- Simulation - rapidly becoming extremely important or foundational to a good robotics program, especially one built on learning. This often has a lot of overlap with games programming so this can attract a certain type.

Roughly speaking, if you decide you like one of Sim, Controls, Planning (what kind?), Proprioception, Exterioception/mapping, Tracking, or Systems, you should tailor your coursework and projects to match.

Oh and I should mention - once you pick one of these, they are often very different when you are working on wheeled vehicles vs legged ones vs aircraft vs spacecraft vs plain-old-arms/ manipulators. But the skills are transferable so learn strong fundamentals.

Anti-recommendations:

- LLMs. I have heard they are going to be helpful, but are just hype so far. Skip for robotics AFAICT

- UI/UX. Everyone says they are going to invent the easiest-to-use automated system, just as soon as it "works". Spoiler alert, just like Akins laws of spacecraft design, if your system involves building a robot to build some other product, you are defacto a robotics company and will spend all your time making the robot work.

There are very few "Generalist" robotics positions -- you'll be competing with PhDs who are specialists but picked up enough experience doing their PhD to have generalist level skills. You want to be on a specific team doing a specific thing deeply. It's also the most fun to be on a specialized team!

Remember, there are two hard problems in robotics: Perception and Funding. So Simulation, Proprioception, Exterioception, Mapping, Prediction, esp Vision (nowadays) are hugely important to the success of a program. As a planning guy, the rest is "easy".

[spieswl]

Hugely bullish on the domain.