Totally free, don't need to buy anything just a computer.
I've been designing electrical hardware for robots for the last 4 years for a big corporation and I can tell you, the fun and money is in the software but having another skill is awesome. Robotics is a place where multiple fields converge and if you find a good team they will help you to grow.
Embedded is the adjacent field after you complete the course. Maybe something like zephyr project.
If you want to get you feet wet with mechanical. Buy a A1 mini and play with onshape (www.onshape.com) to design your first pieces, supports for the motors or the board, try create you own gripper.
As for the electrical engineering, is the one with most pitfalls and the most expensive. A wrong voltage will release the magical smoke and is another 30$ for a board. Tread carefully. Start with the RP2040 or the RP2350, they are cheap and well documented. This skill will evolve hand by hand with the embedded coding. Start small. Learn about H-bridge and brushed motors before doing the jump to the bigboys and FOC control with brushless. Get a cheap soldering iron. If you can, a clone of the JBC C245 tips. Is the most versatile and you can find stuff in alie xpress for 45 or 50$ and would be similar to the tools you will find in the field without breaking the bank.
Search for ROS meetups. I could point you to some depending where in the world you are.
And above all, it will be a long journey. Don't dispear, do at your own time but don't forget the objective.
I'm in the field and I disagree with the initial direction of this post. You aren't going to 'learn robotics' in a meaningful manner by checking the boxes in a online ROS2 course.
Robotics is a compound discipline which pairs mechanical and electrical engineering knowledge with mathematics and software development. In order to get meaningful practice in all of these areas, I would recommend re-implementing a robot vacuum from 'scratch'.
The actual vacuum part is non-essential, as you're really trying to implement the famous 'turtle' robot and experience all the design steps/compromises/challenges first hand. As a goal, aim for autonomous navigation around your home that works equivalently to a cheap 'throwaway' robo-vac.
Keep in mind you are surrounded by robotics. Most passenger vehicles, consumer drones, micro-mobility devices and modern construction equipment are 'robots in varying degrees of disguise'. Practical knowledge regarding any of these systems transfers well if you know where to apply it.
It's similar, but the advice should be good for a software professional. It's an actionable, well-documented goal which takes you through the basics you're likely to care about. If any step needs some extra explanations, the choice of project guarantees you can find hundreds of good resources for that step in particular. With that basic background, next steps will be easier to find and understand.
There was no advice provided other than to "look it up". That's not particularly helpful for someone new to the field and overwhelmed by the amount of resources and approaches. If you are aware of "documentation" it would be more useful to provide links to such resources for someone just getting started.
A solid resource for me getting started was the textbook Probabilistic Robotics. It may not be state of the art but I feel it is a great resource on the topic -
I did a very basic version of this and it was a lot of fun. I bought a chassis online with tank treads that each had a motor. I used an Arduino to send the signal to each tread to turn and a distance sensor so it knew when it was arriving at an object. If it sensed that something was in front of it, it just turned 90 degrees and kept going.
Super simple but it felt like a big accomplishment to get that far.
Where would you recommend someone to start from a more data-sciencey background, algorithms like VSLAM look interesting to mess around with but building a whole robot just to do so seems daunting.
> And above all, it will be a long journey. Don't dispear, do at your own time but don't forget the objective.
My biggest issue with robotics is that I don't see the point in any objective.
Building a cool robot feels like it's just a toy to me, and I don't know how to get around that feeling. I studied mechatronics at uni and spent a long time learning on my own in addition.
Robotics for business is almost a cliff, very hard to get into and make something that works reliably at a reasonable cost, from a solo developer point of view
>very hard to get into and make something that works reliably at a reasonable cost, from a solo developer point of view
I mean yes, otherwise they'd be even more robotic stuff wandering about
In products they have the trade off triangle where you can pick things like fast-cheap-good, pick any two.
In robots it's cheap-reliable-featureful pick any one.
The problem with the term 'cool' is it sets no boundaries. Those constraints limit your costs and scope. That's the hard part for most people when they think about cool.
And reliable is more of a time factor (+effort). QA on products takes a massive amount of time and effort to figure out what is not reliable.
> As for the electrical engineering, is the one with most pitfalls and the most expensive. A wrong voltage will release the magical smoke and is another 30$ for a board. Tread carefully.
I enjoyed reading "Exploring Beaglebone" by Derek Molloy a few years ago, because the book has sections "how to destroy your beaglebone" and "how to interface with electronics". The website seems broken. The book's ISBN is 978-1-118-93512-5. Some of the recommendations there (voltage clamping circuit on the 1.8 V analog inputs) can save your board.
Microcontrollers and PLC are historically different fields that have some overlap as the fields converge somewhat. PLC come from relay logic and so learning Ladder Logic and playing with a cheaper Automation Direct PLC might be good if you're looking to do control systems like industrial machines and those robotics. RPi series micros are good to learn embedded electronics, servo controls and Realtime OS. Computer Engineering and Control System Engineering are treated differently even in the California State Engineering License Exams, so they tend to be different paths but the skills have some overlap. My degree was in computer engineering and didn't cover any PLC, but I contract and PLC comes up a lot in one-off things that need to be reliable.
Yeah. As some has said already PLC are more oriented to robotic arms in factories etc, where space is not a premium. Robots like anymal from anybotics, spot from boston dynamics or the unidog from unitree to name a few don't use PLC at all due to lack of space. Also energy efficiency, mcu at most will push less than a watt to move something complex, a motor control for the FOC, I mentioned earlier.
I worked for the past 4 years in HP siteprint.The main problem was developing all to fit inside a pelican case that you could check in on a plane. The smallest PLC was almost the full internal volume of the robot. That's why I said microcontrollers, more ready available to experiment at home, faaaaaaaar more cheaper and those two, very well documented. STM32 in europe is the big player but is harder to get into, the documentation tends to be cahotic.
Though by total coincidence, it looks like I'm about to inherit responsibility for a fleet of Raspberry Pies that manage dashboards on a factory production floor. But they are older, and it's probably just going to be like managing any other low spec Debian server, albeit connected to a monitor.
Mmmm true, but will not replace a good coder. The software team has been experimenting with AI. Is useful and can guide you to do a Proof of concept fast but if you want to start doing very specific custom stuff all crumbles down fast.
In the next years? Yeah I see resolving path planning without a doubt or reverse kinematics or object recognition, for example. AI will be another tool, one you have to learn to use it. But replacing a full software guy... I don't see it, to be honest. I see it more like in the novel Beyond the Blue Event Horizon. The first chapters explains AI as the AI agents that are being rolling out nowdays. But they will be more like what a junior engineer is to a senior, more than replacing a full team of engineers.
All we really need for the robotics AI revolution is to deploy many tens of thousands of well built, cheap, reliable robots sold at a profit that customers get tons of utility out of, get petabytes of data back from them while complying with data privacy regs, train a model on this data on a few thousand H200s, and then deploy that model back to the robots, repeating the cycle every few weeks. The rest will be easy.
AI trivializes coding: the complexity and scope of robot software will increase.
Robotics-oriented ML trivializes current robot design problems: demand for robotics engineers increases, the projects do cooler things but the day-to-day gets less interesting.
Robotics is definitely getting more accessible! But keep in mind it’s a whole different world from traditional web or desktop software development, so don’t be surprised by the relatively steep learning curve. Keep at it though!
- Buy a small robot kit from Amazon or a local reseller. Yahboom make some good robot toy car kits. Hugging Face have the open source SO-ARM101 that plenty of companies manufacture and sell now. Expect to spend about $250 USD including a Jetson Nano for a good kit, up to $1000 USD if you want some more sensors
- If you can’t afford a real robot, play around with simulators like Isaac Sim and Mujoco
- Check out LeRobot, excellent framework for ML robotics from Hugging Face
- Learn the basics of ROS
(pubsub), even if you don’t end up using it, a lot of the industry jargon and design patterns come from ROS so it helps to understand it. Think of ROS like Ruby on Rails, it’s a heavyweight batteries-included framework with lots of opinions.
- ROS does have some nice libraries for manipulation (MoveIt) and navigation (Nav2) using more classical (non-ML) methods
- Leverage AI tools such as ChatGPT and Cursor when you get stuck, it’s a lot faster than Googling when you’re just getting started and don’t even know the right term to search for.
- (Shameless plug) Check out two tools I’m working on: mcap.dev for logging and foxglove.dev for visualization
I highly recommend starting with the SO-ARM101 and the LeRobot tutorial. They're super cheap, its insanely quick to get started, and you can even buy pre-made kits like at https://partabot.com . It's the "Hello World" of robotics now, imo.
Don't bother with a Jetson Nano, you don't need that to get started, and by the time you need that you'll know a lot already. You can just drive the robot from your laptop!
Getting to training your own VLA fine-tuned model is a super quick and easy process. You can see examples of other people completing the tutorial and uploading their training/evaluation datasets here (shameless plug for my thing): https://app.destroyrobots.com
I wouldn't bother much with ROS at first tbh. It'll bog you down, and startups are moving toward using other approaches that are more developer friendly, like Rust-based embedded.
You can go far with a robot connected to USB though!
Maybe ROS is the way to get started in robotics and for AGVs it's probably the most resourced thing one could learn.
But that is really only for AGVs. Once you get into the air, it's all Mavlink (always has been), ASVs and AUVs still run MOOS, and robotic arms are far more likely to use ABB studio than Moveit and the research is going towards LeRobot with end-to-end control, not classical methods. IoT systems are mostly Home Assistant, and well, some just use MQTT directly instead.
ROS is probably not as ubiquitous as us ROS devs would like to believe, what one should learn really depends on the field one wants to be in.
ROS is still very heavily used in industry and is growing in absolute terms, but most of the newer frameworks and research are learning towards e2e methods.
But even if you don't use ROS, it really helps to have a working knowledge of how it approaches things like pubsub, logging + replay, transforms, etc.
The idea of that game is that you build vehicles to do rescues and deal with natural disasters. While there is a career mode where you gain currency that you can spend on parts and fuel, most people who play that game play it in sandbox mode where you essentially design vehicles to do certain things, while also configuring the game to chose missions it generates. For example, you can make it so you only have to deal with land rescue missions or only fight enemy ai.
The building system is VERY in depth. While you don't have to worry about structural strength, you do have to keep things in mind like part placement, CG location, internal volume for buoyancy for ships. Then you get to propulsion, which you have to build out of components - the game has a fairly indepth internal combustion engine simulator where you build custom engines, and have to make sure they are fed with adequate fuel, air, and cooled appropriately. You can do jet engines, you can do nuclear, you can do full electric, and so on.
Then you have to build systems to do missions - for example, to transport a container you have to build a crane to be able to pick it up.
Finally, the game features a microcontroller system which is the bread and butter of doing cool things. There is a bunch of sensors that can read data (GPS, laser distance, pitch, roll, heading, radar, e.t.c), which you can route into a microcontroller, and do math either with logic blocks or Lua code, and thats how you build automation. You will get very familiar with things like PID controller tuning, trigonometry math (for things like distance sensing), state machine coding practices, and other things that are all applicable to the real world.
Start by deciding its purpose. The form will follow the purpose. If you know electrical engineering, you won't make as many mistakes as I have. If you know mechanical engineering, you won't take as long to design the components as it took me. If you're a competent programmer, you won't be as slow integrating the hardware into a cohesive whole as I am. If you've read The Design of Everyday Things, you're ahead of the curve in terms of making it accessible.
I'm not joking, but some of those Lego robotics kits can work just fine for getting your feet wet. Yes, even if they are made for kids.
When I started out, it was with microcontrollers, breadboards, sensors, actuators. And even though it was in college, I do wish I had just played around with more high-level stuff first.
The lego mindstorms kits were great for this. Nice and modular for the hardware, but still real enough to teach you lessons like sometimes identical motors don't work the same way.
Although the Mindstorms line is discontinued, nowadays there's the Lego SPIKE Prime (it's marketed more towards classrooms). Like the Mindstorms EV3, you can program it with either a visual block language or MicroPython.
All the responses, most of which I've seen are great, are very software focused. I get it, makes sense for HN. There is a whole world of hardware in this space. Learning how to design mechanisms that work, and last. Custom motors, controllers, actuators, hardware.
For that there are some great points of entry now. Places like pololu robotics, Adafruit, sparkfun, etc. are all as good as ever and are great jumping off points into building and eventually designing hardware.
Robotics is more accessible than ever. The tech is here to build almost anything you want. Dream big! We can now buy cameras for a couple dollars, microphone arrays, sensors, motors and drivers. 3D printers are everywhere, stock components also available.
Or 'manage your expectations', download ROS and build another mediocre turtle bot powered by some Nvidia Teraflop chip (if they allow you to boot their sdk), and spend a year learning "abstractions" defined by other people for other projects.
And if you're in high school, join a First Robotics team. (In First Robotics, teams build a moderately large robot that can zip around a field, grabbing things and shooting balls for instance. It's like a competitive sport but with robots competing. The robots are controlled by drivers, but can also act autonomously for more points. The task is different each year, with sub-tasks of varying levels of difficulty, so teams with widely different skill levels can take part: some robots are very simple while others are amazingly complicated. It's a great way for high schoolers to learn engineering skills, anything from programming to mechanical engineering.)
I would say for starting a first robotics lego league is going to be easier to access because they build a smaller robot out of legos, plus the "season" starts in the Fall vs. January for First robotics league.
I've coached a First team that has qualified to go to worlds the last four years and been on the Einstein field once in that time. I think you'd learn a few things
- robots are built to solve problems and the most technically complex and advanced robots don't always solve problem better than simple elegant designs.
- Robots involve multiple skills and usually get built by teams where members are specialists in specific fields. Some people will understand all of the robot sub systems but
FIRST and most of its teams are very open to collaborating and supporting rookies new to the org. I recommend reaching out to as many nearby teams as possible and see what support they can provide. Any serious teams are motivated to help as this directly contributes to their team's success during the competitive season. Competitions require a teams to have a pro-social aspect to their operations. Helping other teams is a strong signal in this area.
Additionally, find a nearby FRC competition and volunteer for at least one event (do more, if you can). Wander the robot pit and interact with the teams. There will be a lot of good intel for you there just wandering around and asking questions.
I couldn't agree more. FIRST is an excellent organization to get involved with. Even if you don't have specialities which directly align with the needs of a team, most will not turn you away (especially if you demonstrate passion).
Just a few thoughts about starting a team and/or volunteering:
Starting a FIRST Robotics Competition (FRC) team is not for the feint-of-heart and requires significant time and money investment. This is the sort of endeavor you try when you're either retired or have a group of other dedicated volunteers willing to help you build the team over multiple seasons. If you spend a year or two mentoring/volunteering for a well-established team, you'll get a good sense of what you're getting into. FRC is a bit hardcore.
If no FRC teams exist nearby, FIRST Lego League (FLL) is a good entrypoint, but may not be technical enough for an adult interested in using FIRST to gain exposure to robotics. (It is plenty satisfying to mentor these teams, but Mindstorms can be somewhat limiting.) These are geared toward using Lego Mindstorms for learning robot concepts.
A good middle ground (for exposure to more practical robotics) would be volunteering with a FIRST Tech Challenge (FTC) team. It's the middle ground between FLL and FRC and is _doable_ for a single, dedicated, passionate adult to start (though I'd strongly recommend finding another volunteer to pursue this with).
If getting involved with a team is not an option, seek out nearby FIRST events that you can volunteer at. Many competition events need volunteers and you'll get a chance to interact with local teams and find plenty of opportunities to play with robots.
Two bits of advice: just jump in, and set reasonable expectations for yourself.
Robotics is a field filled with layers upon layers of complexity, theory, and real-world problems. Those at the top of the game (think robust dog robots, walking bipedal star wars droids, high-speed and high-torque many-DOF arm platforms) are leveraging learnings and expensive prototypes from decades of work/research to achieve those feats. This is not to be discouraging, but to say - they all started somewhere - you too can start, and maybe you won't build things like that today, but you can get there.
And the cool thing is all that robotics work by experts has made the barrier to entry much lower - today you can choose to apply money to solve problems you don't want to learn and focus on the things you do want to learn, in ways that weren't possible 10 years ago. Need a powerful closed loop motor system? Buy an ODrive or closed-loop stepper platform off the shelf, and focus on how to apply those systems to build something higher level.
But the big difference with learning hardware/robotics compared to software (speaking from experience having watched a lot of really smart people struggle to get robots working when I ran an MIT robotics competition, 6.270, and was a lab assistant for another course, 6.141) is that the real world is unforgiving in a way that software is generally not. So if you come from a software background, you will find that robotics can have so many more setbacks because nothing ever moves/behaves/reacts in a precisely predictable way in physical space. This is why I say just jump in - you'll have fun learning all the ways things go wrong, and they faster you get that learning out of the way, the sooner you can build things that work reliably!
Try things and figure out how and why they don't work, and iterate. But don't set unrealistically high expectations or it will just be frustrating.
1. Start by learning a simulation tool, e.g. Mujoco (open source) or Isaac Sim.
2. Learn basics of optimal control and reinforcement learning, reproduce papers/ideas in the simulation.
3. Get your hands dirty on a cheap robot, and try deploy your trained model on it. For mobility and manipulation. Unitree Go1/Go2 for mobility, and robotic arms for manipulation.
1) Get a 3D printer (or access to one). Or visit your local art supply store (for structural basswood) and hardware store (for nuts and bolts).
2) Get an electronics starter kit. (Adafruit or SparkFun are good places to start looking.)
3) Buy/borrow the book "Practical Electronics for Inventors". You don't need to read it cover to cover, but it's very useful. (Realistically, though, an LLM is probably good enough to explain basic concepts and/or help you pick parts these days.)
4) Build a toy robot with parts you printed (or purchased) and parts from the electronics kit.
5) Once you've built the toy robot, make something bigger! (or the existing one better!)
6) Optional: Find someone to buy your toy robot so you can have the funds to design and build your next one.
I'm reading this and kind of stuck on the 4th. I have a printer though not much of 3D designer. How do one get 3D models for parts that is suitable with SparkFun electronics?
For electronics, all you really need to get started is an Arduino, 3 hobby servos, and a breadboard and wires. The first robot I sold was basically just that. And the physical parts were Lego-Technic compatible laser-cut (later 3D printed) beams. (https://bitbeam.org/, https://www.thingiverse.com/thing:11747)
Start making your own "lego" then go from there. This idea can get you pretty far --> https://bitbeam.cc/en/
Adafruit is your friend. Get one of their feather boards, an imu breakout, motor controller and then a simple robot chassis + motors from Amazon. Code in circuit python and save yourself the build chain and debug hell that is traditional embedded programming. Circuitpython / micropython is great, well supported, and makes embedded programming more fun. You’ll encounter the haters see it as training wheels but trust me, it’s great.
Edit: you could take a more top down approach and get like an ardupilot, use it in rover mode, and just really learn how to configure and use it to its full potential which is pretty far out there. There’s also a lua scripting capability last time I checked.
It's not more accessible than ever. If you want to make it in robotics, you're going to have to read research papers and preferably have attended as many robotics related courses during university as possible. The hobbyist scene is big, but the vast majority of robots are basically fancy toys and almost no one ever goes beyond simple PID. The problem is that robotics is clustered around industrial robots and academia with nothing in-between. Unless you have the necessary background, you will most likely be stuck scraping the surface simply because you're not aware of the most recent developments in those areas.
If you want to understand how it works, take first Stanford's CS223A and then MIT's 6.832 Underactuated Robotics courses. They have lectures online as well. Udacity's Self-driving Car Nanodegree might be a good idea after those two.
From the electronics side, the path towards control theory is a lot of math (signals and systems, Fourier transforms, transfer functions, feedback and oscillations, compensation circuits) ultimately leading up to the student solving the inverted pendulum problem sometimes in early Masters degree region or maybe the advanced student Bachelor's degree.
I'm not entirely sure how to make that more 'accessible'. It's like, spend the next 5 years of your life mastering difficult math and electronics so that the sensors can be integrated into feedback that stabilizes a motor system.
I guess you can cheat and use servos for a lot of this (where an EE already solved many feedback loop issues). But if you ever need to build your own sensor+motor solution you'd get stuck if you didn't know the math.
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Making simple controls without relying upon feedback sensors is likely the goal, you can do a lot with that. But then do your best to avoid the Masters level demons that plague this problem set.
Maybe learn PID controller theory and if that isn't enough for your problems, give up and try a different design. PID is simple enough that you won't need years of math to learn, but it's very adhoc to configure and not always the best methodology to use.
I've just started this journey. I always wanted to get into electronics and robotics, but instead went the software route. I've picked up an Arduino and microbit over the years, but they sit collecting dust.
It may sound silly, but I asked Gemini to recommend a learning plan and it came up with a detailed plan along with time estimates in months. The first step is reading and going through all the exercises in Make Electronics (third edition) which is very hands on.
When I took the robotics course in grad school, we spent so much time on inverse kinematics and other complex math. It was pretty intense and gave me the perception that robotics was pretty difficult.
Yet, today, people easily build simple robots using a few rc servos and an Arduino. Somehow kinematics is not really essential if you just want to build simple robotic toys. The pedagogy of robotics courses could have been so much better...
Many robotics tasks can be solved by linear motors and grippers. Not everybody needs to make 6 DoF arms. Nor they need machine-learning enhanced optimal control. Grad schools prepare you for the basics of the hardest possible systems.
On the engineering side the number of difficult problems with robotics is enormous. Even the simplest systems will fail pretty badly outside lab. No two robots will work the same. As a grad student those are the things you learn on top of IK at work. So if you get employed for designing actual 6+ DoF systems and missing the theoretical stuff you'll be way behind.
However, for self teaching and hobby stuff, just making a simple robot work reliably is still a difficult task with lots of learning potential. It may not cover complex arms but you may actually gain knowledge to solve the engineering part of the problems which is a huge boost for theories.
Don't do a degree or two like I did. Just build shit, get yourself a 3D printer and some electronics, and again just build shit.
The only maths you'll need at the beginning is basic control engineering (PID Loops), forward/inverse kinematics and Extended Kalman Filtering. The only other thing is maybe V=IR, anything else and you're just placating some professor's ego.
It's not that hard to get started! I make robots like this (that one's just to enter the wiring stage) using alu extrusion beams, some 3D printing, off-the-shelf servos and SBCs:
Modern SBCs are decently powerful and run for long enough off a standard drone LiPo pack that you can fairly easily build yourself a solid little platform to learn and experiment with different controller approaches. Stereo cams, LiDAR modules, etc. are also readily available at a quality level that is decent enough.
You'll quickly realize the amount of work needed to bring any of the more advanced approaches to a productization level, but a "I implemented enough of this to get the principle" mini-Boston-Dynamics is in reach of the hobbyist.
In fact, the programming craft aspect of all of this is relatively simple. Basic implementations are typically not architecturally complex or a lot of sloc. You'll find that it's more about learning some control theory, and it'll also get you into machine learning.
Robotics is a large multidisciplinary area, comprising of parts of ME, EE, and CS fields. Before you go down a particular path, it may be good to step back, and note down things which you actually enjoy doing, and how they might relate to one or more of these fields. After all the drama wears off and you are up late working on something .. it's important to enjoy what you are doing. Not just trying to catch some hype about the next big thing or the tech giants or AI or whatever (or something your friends or parents told you).
The top comment refers to a course around a small mobile robot. Maybe you could go through this, and try to build a bicycle which would balance itself and drive a 100 yards in an empty, safe parking lot. That will certainly involve ME, EE, and CS! Who knows where that might lead?
It’s incredibly easy but for some reason seems hard
But no matter what you need an actual physical robot I have never once seen anyone actually transition into robotics without them having made the commitment of spending $100s or $1000s on a capable robot. Very capable robots are in that range at this point.
1.Figure out what you want the robot to do. This is the hardest part, cause it requires constraining your desires considerably
2. Figure out how you want to make it do that. Do you want a deterministic robot? Do you want a robot that uses inference?
3. Then buy the robot that can do the physical action. If your task is to move groceries from your car into the house, you have much different requirements than if its a linear actuator flipping a static switch
4. Choose your robotic actuation path: Dedicated embedded controller (FPGA, PLC), controller coupled with another switch, autopilot etc…
A good starting point is learning to use ROS https://ros.org/. Once you learn ROS you can interact with/use a wide variety of robots. Robotics is a fairly multidisciplinary field though, so it really depends on what area of robotics you are interested in.
The electronics learning is always going to apply to start there if you need to, then depending on your goals the hardware and software will vary.
For simple DIY projects I'd start with getting an Arduino or Arduino compatible board and just play around with building things with sensors, LEDs, motors, etc. You'll find lots of kits and resources online for simple Arduino projects.
More complex projects are probably going to need to be Linux-based (AI, machine vision, etc). In which case you might want to look at building something with a mini PC, Raspberry Pi, NVIDIA Jetson.
These days robotics is super accessible, but can cost a bit depending on what you want to do... That said, most of the time you'll find there are cheap ways to build POCs to validate your ideas first.
In all honesty I’d try and model a 2d 3-link arm in software with forward and inverse kinematics. Then I’d model the inertia of the bars, and model DC motors to apply a torque to the bar interconnects. I’d then model PID controllers for each motor to smoothly move the arm. I’d then move to 3D. Once the physics is modelled you’ll find speccing the motors, solidworks, motor drivers, and MCUs relatively straightforward if you have some basics in electronics.
The fundamentals of robotics is in the math; think control theory. Don’t over emphasize the surface level like ROS, arduinos, and Lego kits. Those are implementation details
Snoozefest for anyone looking to get hands-on. Arduino kits can be had for $50 and then 50 lines of c++ will have basic forward kinematics on a ~10 inch arm you can play with in the real world.
I’ve been playing a bit with toy robots and vision models and I can’t shake the sense that somebody has got to be close to simplifying the control game with high fps cameras. Why are there so many systems to control motors and ground positioning … shouldn’t it all be cameras on the arm figuring out if the motors have positioned the arm correctly and updating to fix?
This is obviously naive and computationally wasteful but I really want to see vision first rebuilds of most control and feedback systems.
Biological analogies are always a bit dodgy, but biology hints that this doesn't work very well. Vision is important, particularly for path planning, but the immediate feedback of proprioception and touch is more important for stability. Think of how hard it is to walk normally when your leg has fallen asleep --- your visual cues remain unchanged, but you lose the immediate feedback loop from your leg. You can do it, but your gait is very unnatural and inefficient.
The best way to learn is just by running small experiments and being curious about the field.
Just a few weeks ago, along with my partner i started this Sunday experiment of building and learning robotics as a software engineer.
We ordered a one hand robotic arm with orin nvidia gpu to start running experiments.
to commit and make it a habit, we also started documenting our learnings and experience.. if this motivates you you can check it out here - https://youtu.be/pAwkl6zd0ws
I was just digging out this Roomba I modded with a Raspberry Pi and camera. I think the cost of that setup was like $40. I meant to get my kids into robotics but they lost interest ... so this cool platform is still sitting around...
Everyone is jumping the gun here. You just haven't told us enough.
How much time do you have? How much do you know about hardware and software? What do you want to do? How much money do you want to invest? What do you want to learn?
The path forward changes entirely depending on the answers to these questions.
Has anybody tried Crunch Lab's HackPack? It seems it could be quite well suited for this purpose -- they claim to make it straight forward to go beyond the kit, and they've certainly taken some of the right steps in that direction.
I tried it. First kit was speced with cheap parts that didn’t really work. Got a replacement kit - same thing. Overall a really disappointing experience. I cancelled and bought a 3D printer, which has been great fun.
A really top-tier robotics engineer is going to be a generalist across mechanical, electrical, and several software domains, and then also a specialist, deep expert in one or two of those. So I'd recommend doing a bit of everything then picking a specialty to learn in depth. Build a really simple kit robot and then program it to do simple stuff using ROS. Write a few ROS nodes from scratch to do something simple, things that existing ROS nodes already do. Then learn why the STL ROS options are (most likely) better than yours.
I strongly recommend taking the generalist approach. It makes you a much better engineer in the long run. I had a friend call me up enraged one day. He got woken up at 1am and ordered to drive across the state to get a site back up and running because his hardware was broken and the very expensive software team was sitting around wasting their time. So he got to the site at three or four AM and found that the room full of software engineers, three PhDs among them, didn't understand that BOTH of the battery terminals needed to be connected. Yes, batteries in fact have a positive and a negative. And these people were each getting paid twice as much as him. He left that company and became hardware leadership at a much better company, thank goodness. My point is, super-specializing in the most profitable hyper-niche right off the bat is going to make you a very mediocre robotics engineer who might be successful in the short term, but might find yourself unemployed in a few years when we find a better modality to replace your hyper-niche. Specialists win the sprints, generalists win the marathons.
Yes, if you can get okay at printing, the friction from idea to implementation dissolves quite a bit. If you're building POCs, it doesn't matter than this gear won't work be durable or that chassis is ugly. Having it in hand for pennies means you'll actually build your idea. It's much like using packages in software. Maybe they aren't perfect fits for what you're building, but they get you close enough. You can refine later once you know the system works. The gap between idea and implementation is so dramatically reduced that it doesn't matter.
Right, so instead of getting involved with the basics or foundations of robotics, the OP should spend a lot of time and money investing in a 3D printer, learning the nuances of 3D printing, and ... for what exactly?
As someone in the industry (I literally can call myself a Robot Master having a Masters Degree in Robotics), these simple “kid kits” are phenomenal. When you first start out, the hardest part is knowing the hardware is actually going to do what you tell it to do. Simplifying the mechanical engineering/electrical engineering so you can immediately create real world actions makes a huge difference in giving you motivation to keep going.
Once you have the basics in place and you understand mechanisms, sensors, and some algorithms, you can move on to other parts of robotics.
However, keep in mind robotics is really about system thinking… you have to understand trades between sensing, thinking, and acting. But most importantly you have to remember you are dealing with the real world… you can’t as easily write a unit test and know that a particular actuator will behave exactly the same way every time.
There are many ways to start with a more academic knowledge of robotics. Courses, ROS, Programs etc. Just picking one is a fine start and you will learn something, but you may not have fun or appreciate the context for what you are learning, which makes it hard to care.
It also depends on what you're trying to learn. Programming? control? electronics? mechanism design? There are many different aspects that require their own expertise. I personally think of a roboticist as someone that can be functional in all the disciplines and bring it all together. Some one that can build a robot from scratch.
This advice is targeted towards someone starting in robotics with an emphasis on building a totally custom robot. You are doing the whole thing from scratch, no kit. (kits are super useful, but I personally like building everything and making hardware that works for me). In my eyes, if you haven't built it in hardware, it probably isn't a robot.
As a research roboticist, my best advice is forget Learning it all up front and just start building. You will probably have strengths and weaknesses, but robotics is a very multi-disciplinary problem and at the start, requires some head banging in what we like to call integration hell. Just Trying to build something does a couple things. It gets you acquainted with the interaction of all aspects (mechanical, electrical, software) of a robot and how they interact. Most importantly it gives you context for sll the things you learn later on. Build something, come across a problem, and google/brute force your way to a solution. You will stumble across context relevant resources and lessons in the moment. Especially at the start, a more "formal" education is too broad and comprehensive for the curious roboticist.
My simple advice is to just come up with something simple and SEND IT!
For mechanical - Onshape for 3D design (free tier) and a bambu A1 mini 3d printer can get you building anything you want for <$400. A couple nights of CAD tutorials will get you started. Hell you can even start with cardboard and hot glue if this is cost/time prohibitive.
For electronics - Browse www.adafruit.com or www.sparkfun.com for sensors and microcontroller boards. They both support QWICC connections which makes getting sensors plugged in and running super easy for a beginner. For computation and control a basic Arduino Uno or one of the adafruit feathers will do just fine. Don't get caught up in the internet debate on what the best microcontroller/single board computer is. The best robot is one that works and it is VERY easy to get in over your head in this realm and fall into the premature optimization track. Better to get something working that under performs than to never build at all.
For software - Most lower level robotics uses c++, which I think scares people. It is mostly because it is one level above hardware. Arduino/common libraries take care of all the hard stuff and you don’t have to worry about large scale things like garbage collection, memory leaks, or efficient code off the bat. The websites above have libraries, examples, and tutorials for every sensor. Even a non programmer type can smush the example code together in a functional way and get something up and running.
As you try to build you will learn and get more complicated. Robotics is so vast and large its best to focus on learning the skill you need at the time. But my main advice is just go build the thing and the learning resources/skills will present themselves when they are needed. Otherwise it is just too much to take a more planned approach.
Great, you know what you want to make. Go ahead, and do it. Look at projects previous folks have done, see how then can be adapted for your need. If you are interested in getting this One Amazing Thing working, great! You have the motivation and cranking through what you'll need to lean to succeed will be possible.
IF, on the other hand, you want to make 1e6 of these things ("tech giants seems to capture most of the conversation")-- that a completely different story. You're going to need a skilled team, ideally one that has been to a rodeo before. I can't help you there.
But if you're building one, for fun --- Just DO It. Ask friendly robotics club members when you get stuck. IF your problem is particularly and singularly unique, then whatever domain that entails, you will need to master; that's your Secret Sauce.
Ivan Sutherland, who was Thesis Advisor to CMU's first Robotics Institute PhD said something to the effect that after 4 years of a Robotics PhD program, you end up with the ability to solder and attach connectors with a high degree of confidence.
A True Roboticists requires deep knowledge in mathematics, software engineering, mechanical engineering, manufacturing small lots, reliability engineering, materials engineering, data collection & graphical evaluation methodologies..... What one might call a Systems Engineer's handbag. It also helps to be inspired by the wonders of nature that biology affords us.
The details? eh, they change. Whether you used some hot cpu, some hot language, some hot OS --- Marc Raibert's hopping & jumping robots used C and BSD4.3 Unix, with the kernel locks cleaned up (reduced) so a 1 kHz kernel interrupt stream could be supported on a 1 MIPS machine (Vax 780). Timesharing was never stopped, but the kernel did get quite a large percentage of CPU cycles.
I'll repeat: Just do it. Start. Move forward. The project will teach you the questions you must ask.
I knew Dean Sutherland at CMU, nice guy. And dad was right. Turns out an advanced grad-student software group had brought me in (back in 2004) because their grad students couldn't build reliable software for the real world, and their military "research partners" were getting rather p.o.'d.
But I'm a non-degreed Mechatronics Systems Engineer, in the truest sense of the word. I'm old enough to predate software engineering programs.
I learned robotics and automation because I was curious, it fueled my ADD, and I kept at it... in the beginning I used plug-in cards for the IBM PC, but I knew basic electronics as a hobby (ham radio, telephonics, heathkit, etc.) and I devoured books. Anything I could get my hands on. Especially Byte magazine and Steve Ciarcia's Circuit Cellar columns.
So get copies of Forest Mims III stuff, and get an arduino or raspberry pi (you can even get/run Codesys on a pi, to learn PLC stuff) and get magazine issues/books from Make: and watch lots of youtube from ElectroBoom and AvE and get your hands dirty.
Remember, you can be skilled at robotics without building Optimus. Currently I'm building and programming high speed mail handling equipment. Not sexy, but it pays the bills and fuels my dopamine. It's all servomotors and sensors and decision logic. And challenging too, paper's moving at 1/8" per millisecond at mid-speeds, you need to be an efficient coder and pre-optimizing your logic, and it's all state machines, all the way down.
Good luck. I make bank, but I'm driven in a thousand directions and I push and I try and while I may be wrong 70% of the time, that would get me into the allstar game if it was baseball!
Never give up, and never surrender! LOL
Do this course https://github.com/henki-robotics/robotics_essentials_ros2
Totally free, don't need to buy anything just a computer.
I've been designing electrical hardware for robots for the last 4 years for a big corporation and I can tell you, the fun and money is in the software but having another skill is awesome. Robotics is a place where multiple fields converge and if you find a good team they will help you to grow.
Embedded is the adjacent field after you complete the course. Maybe something like zephyr project.
If you want to get you feet wet with mechanical. Buy a A1 mini and play with onshape (www.onshape.com) to design your first pieces, supports for the motors or the board, try create you own gripper.
As for the electrical engineering, is the one with most pitfalls and the most expensive. A wrong voltage will release the magical smoke and is another 30$ for a board. Tread carefully. Start with the RP2040 or the RP2350, they are cheap and well documented. This skill will evolve hand by hand with the embedded coding. Start small. Learn about H-bridge and brushed motors before doing the jump to the bigboys and FOC control with brushless. Get a cheap soldering iron. If you can, a clone of the JBC C245 tips. Is the most versatile and you can find stuff in alie xpress for 45 or 50$ and would be similar to the tools you will find in the field without breaking the bank.
Search for ROS meetups. I could point you to some depending where in the world you are.
And above all, it will be a long journey. Don't dispear, do at your own time but don't forget the objective.
I'm in the field and I disagree with the initial direction of this post. You aren't going to 'learn robotics' in a meaningful manner by checking the boxes in a online ROS2 course.
Robotics is a compound discipline which pairs mechanical and electrical engineering knowledge with mathematics and software development. In order to get meaningful practice in all of these areas, I would recommend re-implementing a robot vacuum from 'scratch'.
The actual vacuum part is non-essential, as you're really trying to implement the famous 'turtle' robot and experience all the design steps/compromises/challenges first hand. As a goal, aim for autonomous navigation around your home that works equivalently to a cheap 'throwaway' robo-vac.
Keep in mind you are surrounded by robotics. Most passenger vehicles, consumer drones, micro-mobility devices and modern construction equipment are 'robots in varying degrees of disguise'. Practical knowledge regarding any of these systems transfers well if you know where to apply it.
This feels like the "How to Draw an Owl" meme all over again. Just create a self navigating robot from scratch...
It's similar, but the advice should be good for a software professional. It's an actionable, well-documented goal which takes you through the basics you're likely to care about. If any step needs some extra explanations, the choice of project guarantees you can find hundreds of good resources for that step in particular. With that basic background, next steps will be easier to find and understand.
There was no advice provided other than to "look it up". That's not particularly helpful for someone new to the field and overwhelmed by the amount of resources and approaches. If you are aware of "documentation" it would be more useful to provide links to such resources for someone just getting started.
A solid resource for me getting started was the textbook Probabilistic Robotics. It may not be state of the art but I feel it is a great resource on the topic -
[1] https://robots.stanford.edu/probabilistic-robotics/
I did a very basic version of this and it was a lot of fun. I bought a chassis online with tank treads that each had a motor. I used an Arduino to send the signal to each tread to turn and a distance sensor so it knew when it was arriving at an object. If it sensed that something was in front of it, it just turned 90 degrees and kept going.
Super simple but it felt like a big accomplishment to get that far.
>You aren't going to 'learn robotics' in a meaningful manner by checking the boxes in a online ROS2 course.
This is the best answer-- all other answers are saying "Run this simulation of a robot".
but a simulation is not a robot. Even a simple lego tupe robot kit shows you how fiddly and complex real world moving parts make everything.
Where would you recommend someone to start from a more data-sciencey background, algorithms like VSLAM look interesting to mess around with but building a whole robot just to do so seems daunting.
In that case it doesn't sound like you want to learn robotics - you want to learn VSLAM.
It's like saying how do I learn car manufacturing but really I just want to try to make rubber tyres.
Couldn't you try implement them in a game engine?
> And above all, it will be a long journey. Don't dispear, do at your own time but don't forget the objective.
My biggest issue with robotics is that I don't see the point in any objective.
Building a cool robot feels like it's just a toy to me, and I don't know how to get around that feeling. I studied mechatronics at uni and spent a long time learning on my own in addition.
Robotics for business is almost a cliff, very hard to get into and make something that works reliably at a reasonable cost, from a solo developer point of view
>very hard to get into and make something that works reliably at a reasonable cost, from a solo developer point of view
I mean yes, otherwise they'd be even more robotic stuff wandering about
In products they have the trade off triangle where you can pick things like fast-cheap-good, pick any two.
In robots it's cheap-reliable-featureful pick any one.
The problem with the term 'cool' is it sets no boundaries. Those constraints limit your costs and scope. That's the hard part for most people when they think about cool.
And reliable is more of a time factor (+effort). QA on products takes a massive amount of time and effort to figure out what is not reliable.
> As for the electrical engineering, is the one with most pitfalls and the most expensive. A wrong voltage will release the magical smoke and is another 30$ for a board. Tread carefully.
I enjoyed reading "Exploring Beaglebone" by Derek Molloy a few years ago, because the book has sections "how to destroy your beaglebone" and "how to interface with electronics". The website seems broken. The book's ISBN is 978-1-118-93512-5. Some of the recommendations there (voltage clamping circuit on the 1.8 V analog inputs) can save your board.
Interesting one thing that is more satisfying with robotics is that because you can see your creations in real world
That is sooooooo much true. The pride and joy to see the robot moving, no words can describe the feeling!
How programming of RP2040 or RP2350 could translate to platforms used commercially like Siemens SIMATIC and others?
Microcontrollers and PLC are historically different fields that have some overlap as the fields converge somewhat. PLC come from relay logic and so learning Ladder Logic and playing with a cheaper Automation Direct PLC might be good if you're looking to do control systems like industrial machines and those robotics. RPi series micros are good to learn embedded electronics, servo controls and Realtime OS. Computer Engineering and Control System Engineering are treated differently even in the California State Engineering License Exams, so they tend to be different paths but the skills have some overlap. My degree was in computer engineering and didn't cover any PLC, but I contract and PLC comes up a lot in one-off things that need to be reliable.
Yeah. As some has said already PLC are more oriented to robotic arms in factories etc, where space is not a premium. Robots like anymal from anybotics, spot from boston dynamics or the unidog from unitree to name a few don't use PLC at all due to lack of space. Also energy efficiency, mcu at most will push less than a watt to move something complex, a motor control for the FOC, I mentioned earlier.
I worked for the past 4 years in HP siteprint.The main problem was developing all to fit inside a pelican case that you could check in on a plane. The smallest PLC was almost the full internal volume of the robot. That's why I said microcontrollers, more ready available to experiment at home, faaaaaaaar more cheaper and those two, very well documented. STM32 in europe is the big player but is harder to get into, the documentation tends to be cahotic.
If you've managed to collect some good documentation, links appreciated! Or PDFs (my Gmail username is the same as my HN username) if inclined.
Thank you!
About stm32 or the rp2040?
The ESP32. Thank you!
Though by total coincidence, it looks like I'm about to inherit responsibility for a fleet of Raspberry Pies that manage dashboards on a factory production floor. But they are older, and it's probably just going to be like managing any other low spec Debian server, albeit connected to a monitor.
> the fun and money is in the software
This could change if there are breakthroughs in AI, which is not unlikely in the coming few years. Any thoughts on that?
Mmmm true, but will not replace a good coder. The software team has been experimenting with AI. Is useful and can guide you to do a Proof of concept fast but if you want to start doing very specific custom stuff all crumbles down fast.
In the next years? Yeah I see resolving path planning without a doubt or reverse kinematics or object recognition, for example. AI will be another tool, one you have to learn to use it. But replacing a full software guy... I don't see it, to be honest. I see it more like in the novel Beyond the Blue Event Horizon. The first chapters explains AI as the AI agents that are being rolling out nowdays. But they will be more like what a junior engineer is to a senior, more than replacing a full team of engineers.
All we really need for the robotics AI revolution is to deploy many tens of thousands of well built, cheap, reliable robots sold at a profit that customers get tons of utility out of, get petabytes of data back from them while complying with data privacy regs, train a model on this data on a few thousand H200s, and then deploy that model back to the robots, repeating the cycle every few weeks. The rest will be easy.
AI trivializes coding: the complexity and scope of robot software will increase.
Robotics-oriented ML trivializes current robot design problems: demand for robotics engineers increases, the projects do cooler things but the day-to-day gets less interesting.
Both: this is probably just AGI right?
Robotics is definitely getting more accessible! But keep in mind it’s a whole different world from traditional web or desktop software development, so don’t be surprised by the relatively steep learning curve. Keep at it though!
- Buy a small robot kit from Amazon or a local reseller. Yahboom make some good robot toy car kits. Hugging Face have the open source SO-ARM101 that plenty of companies manufacture and sell now. Expect to spend about $250 USD including a Jetson Nano for a good kit, up to $1000 USD if you want some more sensors
- If you can’t afford a real robot, play around with simulators like Isaac Sim and Mujoco
- Check out LeRobot, excellent framework for ML robotics from Hugging Face
- Learn the basics of ROS (pubsub), even if you don’t end up using it, a lot of the industry jargon and design patterns come from ROS so it helps to understand it. Think of ROS like Ruby on Rails, it’s a heavyweight batteries-included framework with lots of opinions.
- ROS does have some nice libraries for manipulation (MoveIt) and navigation (Nav2) using more classical (non-ML) methods
- Leverage AI tools such as ChatGPT and Cursor when you get stuck, it’s a lot faster than Googling when you’re just getting started and don’t even know the right term to search for.
- (Shameless plug) Check out two tools I’m working on: mcap.dev for logging and foxglove.dev for visualization
I highly recommend starting with the SO-ARM101 and the LeRobot tutorial. They're super cheap, its insanely quick to get started, and you can even buy pre-made kits like at https://partabot.com . It's the "Hello World" of robotics now, imo.
Don't bother with a Jetson Nano, you don't need that to get started, and by the time you need that you'll know a lot already. You can just drive the robot from your laptop!
Getting to training your own VLA fine-tuned model is a super quick and easy process. You can see examples of other people completing the tutorial and uploading their training/evaluation datasets here (shameless plug for my thing): https://app.destroyrobots.com
I wouldn't bother much with ROS at first tbh. It'll bog you down, and startups are moving toward using other approaches that are more developer friendly, like Rust-based embedded.
You can go far with a robot connected to USB though!
Maybe ROS is the way to get started in robotics and for AGVs it's probably the most resourced thing one could learn.
But that is really only for AGVs. Once you get into the air, it's all Mavlink (always has been), ASVs and AUVs still run MOOS, and robotic arms are far more likely to use ABB studio than Moveit and the research is going towards LeRobot with end-to-end control, not classical methods. IoT systems are mostly Home Assistant, and well, some just use MQTT directly instead.
ROS is probably not as ubiquitous as us ROS devs would like to believe, what one should learn really depends on the field one wants to be in.
Definitely! I agree with everything you said.
ROS is still very heavily used in industry and is growing in absolute terms, but most of the newer frameworks and research are learning towards e2e methods.
But even if you don't use ROS, it really helps to have a working knowledge of how it approaches things like pubsub, logging + replay, transforms, etc.
This is by far one of the best ways to learn IMO
https://store.steampowered.com/app/573090/Stormworks_Build_a...
The idea of that game is that you build vehicles to do rescues and deal with natural disasters. While there is a career mode where you gain currency that you can spend on parts and fuel, most people who play that game play it in sandbox mode where you essentially design vehicles to do certain things, while also configuring the game to chose missions it generates. For example, you can make it so you only have to deal with land rescue missions or only fight enemy ai.
The building system is VERY in depth. While you don't have to worry about structural strength, you do have to keep things in mind like part placement, CG location, internal volume for buoyancy for ships. Then you get to propulsion, which you have to build out of components - the game has a fairly indepth internal combustion engine simulator where you build custom engines, and have to make sure they are fed with adequate fuel, air, and cooled appropriately. You can do jet engines, you can do nuclear, you can do full electric, and so on.
Then you have to build systems to do missions - for example, to transport a container you have to build a crane to be able to pick it up.
Finally, the game features a microcontroller system which is the bread and butter of doing cool things. There is a bunch of sensors that can read data (GPS, laser distance, pitch, roll, heading, radar, e.t.c), which you can route into a microcontroller, and do math either with logic blocks or Lua code, and thats how you build automation. You will get very familiar with things like PID controller tuning, trigonometry math (for things like distance sensing), state machine coding practices, and other things that are all applicable to the real world.
Rather than watching videos or reading on the internet, I think its worth it to get your hands dirty.
For starter, I always recommend a RC car with an Arduino (or cheaper equivalents).
Following can be had for less than <$100
- SG90 servo motor - 28BYJ-48 stepper motor - ULN2003 driver board - UNO R3 Controller Board (Elegoo) - RC car chasis/3D printed chasis
Hack around, add sensors, cameras etc. Next would be to build a robotic arm.
Start by deciding its purpose. The form will follow the purpose. If you know electrical engineering, you won't make as many mistakes as I have. If you know mechanical engineering, you won't take as long to design the components as it took me. If you're a competent programmer, you won't be as slow integrating the hardware into a cohesive whole as I am. If you've read The Design of Everyday Things, you're ahead of the curve in terms of making it accessible.
I'm not joking, but some of those Lego robotics kits can work just fine for getting your feet wet. Yes, even if they are made for kids.
When I started out, it was with microcontrollers, breadboards, sensors, actuators. And even though it was in college, I do wish I had just played around with more high-level stuff first.
The lego mindstorms kits were great for this. Nice and modular for the hardware, but still real enough to teach you lessons like sometimes identical motors don't work the same way.
Although the Mindstorms line is discontinued, nowadays there's the Lego SPIKE Prime (it's marketed more towards classrooms). Like the Mindstorms EV3, you can program it with either a visual block language or MicroPython.
All the responses, most of which I've seen are great, are very software focused. I get it, makes sense for HN. There is a whole world of hardware in this space. Learning how to design mechanisms that work, and last. Custom motors, controllers, actuators, hardware.
For that there are some great points of entry now. Places like pololu robotics, Adafruit, sparkfun, etc. are all as good as ever and are great jumping off points into building and eventually designing hardware.
Robotics is more accessible than ever. The tech is here to build almost anything you want. Dream big! We can now buy cameras for a couple dollars, microphone arrays, sensors, motors and drivers. 3D printers are everywhere, stock components also available.
Or 'manage your expectations', download ROS and build another mediocre turtle bot powered by some Nvidia Teraflop chip (if they allow you to boot their sdk), and spend a year learning "abstractions" defined by other people for other projects.
While inspiring, it does sound like there needs to be a less steep learning curve to get anywhere. Small incremental steps and all that.
If you want to make something, have a look at https://huggingface.co/lerobot For hardware check: https://github.com/TheRobotStudio/SO-ARM100
There will be a world wide hackathon in two weeks time, no better way to get started and get to know some people: https://huggingface.co/LeRobot-worldwide-hackathon
If you're in NYC, we'll be hosting folks at the Betaworks offices for the 6/14-6/15 hackathon: https://lu.ma/z3z9ipke
You can buy an old Roomba and cannibalize it for your own project, it's a start.
This is an example: https://youtu.be/mTpkV7xZln0
If you’re an engineer, go volunteer for a First Robotics team, and advise high schoolers on your area of expertise.
And if you're in high school, join a First Robotics team. (In First Robotics, teams build a moderately large robot that can zip around a field, grabbing things and shooting balls for instance. It's like a competitive sport but with robots competing. The robots are controlled by drivers, but can also act autonomously for more points. The task is different each year, with sub-tasks of varying levels of difficulty, so teams with widely different skill levels can take part: some robots are very simple while others are amazingly complicated. It's a great way for high schoolers to learn engineering skills, anything from programming to mechanical engineering.)
I would say for starting a first robotics lego league is going to be easier to access because they build a smaller robot out of legos, plus the "season" starts in the Fall vs. January for First robotics league.
I've coached a First team that has qualified to go to worlds the last four years and been on the Einstein field once in that time. I think you'd learn a few things - robots are built to solve problems and the most technically complex and advanced robots don't always solve problem better than simple elegant designs. - Robots involve multiple skills and usually get built by teams where members are specialists in specific fields. Some people will understand all of the robot sub systems but
I was thinking I’d love to do that when my son gets older. Any tips for a first time coach?
FIRST and most of its teams are very open to collaborating and supporting rookies new to the org. I recommend reaching out to as many nearby teams as possible and see what support they can provide. Any serious teams are motivated to help as this directly contributes to their team's success during the competitive season. Competitions require a teams to have a pro-social aspect to their operations. Helping other teams is a strong signal in this area.
Additionally, find a nearby FRC competition and volunteer for at least one event (do more, if you can). Wander the robot pit and interact with the teams. There will be a lot of good intel for you there just wandering around and asking questions.
Source: Am volunteer judge for FRC.
I couldn't agree more. FIRST is an excellent organization to get involved with. Even if you don't have specialities which directly align with the needs of a team, most will not turn you away (especially if you demonstrate passion).
Just a few thoughts about starting a team and/or volunteering:
Starting a FIRST Robotics Competition (FRC) team is not for the feint-of-heart and requires significant time and money investment. This is the sort of endeavor you try when you're either retired or have a group of other dedicated volunteers willing to help you build the team over multiple seasons. If you spend a year or two mentoring/volunteering for a well-established team, you'll get a good sense of what you're getting into. FRC is a bit hardcore.
If no FRC teams exist nearby, FIRST Lego League (FLL) is a good entrypoint, but may not be technical enough for an adult interested in using FIRST to gain exposure to robotics. (It is plenty satisfying to mentor these teams, but Mindstorms can be somewhat limiting.) These are geared toward using Lego Mindstorms for learning robot concepts.
A good middle ground (for exposure to more practical robotics) would be volunteering with a FIRST Tech Challenge (FTC) team. It's the middle ground between FLL and FRC and is _doable_ for a single, dedicated, passionate adult to start (though I'd strongly recommend finding another volunteer to pursue this with).
If getting involved with a team is not an option, seek out nearby FIRST events that you can volunteer at. Many competition events need volunteers and you'll get a chance to interact with local teams and find plenty of opportunities to play with robots.
Two bits of advice: just jump in, and set reasonable expectations for yourself.
Robotics is a field filled with layers upon layers of complexity, theory, and real-world problems. Those at the top of the game (think robust dog robots, walking bipedal star wars droids, high-speed and high-torque many-DOF arm platforms) are leveraging learnings and expensive prototypes from decades of work/research to achieve those feats. This is not to be discouraging, but to say - they all started somewhere - you too can start, and maybe you won't build things like that today, but you can get there.
And the cool thing is all that robotics work by experts has made the barrier to entry much lower - today you can choose to apply money to solve problems you don't want to learn and focus on the things you do want to learn, in ways that weren't possible 10 years ago. Need a powerful closed loop motor system? Buy an ODrive or closed-loop stepper platform off the shelf, and focus on how to apply those systems to build something higher level.
But the big difference with learning hardware/robotics compared to software (speaking from experience having watched a lot of really smart people struggle to get robots working when I ran an MIT robotics competition, 6.270, and was a lab assistant for another course, 6.141) is that the real world is unforgiving in a way that software is generally not. So if you come from a software background, you will find that robotics can have so many more setbacks because nothing ever moves/behaves/reacts in a precisely predictable way in physical space. This is why I say just jump in - you'll have fun learning all the ways things go wrong, and they faster you get that learning out of the way, the sooner you can build things that work reliably!
Try things and figure out how and why they don't work, and iterate. But don't set unrealistically high expectations or it will just be frustrating.
My suggestion
1. Start by learning a simulation tool, e.g. Mujoco (open source) or Isaac Sim. 2. Learn basics of optimal control and reinforcement learning, reproduce papers/ideas in the simulation. 3. Get your hands dirty on a cheap robot, and try deploy your trained model on it. For mobility and manipulation. Unitree Go1/Go2 for mobility, and robotic arms for manipulation.
1) Get a 3D printer (or access to one). Or visit your local art supply store (for structural basswood) and hardware store (for nuts and bolts).
2) Get an electronics starter kit. (Adafruit or SparkFun are good places to start looking.)
3) Buy/borrow the book "Practical Electronics for Inventors". You don't need to read it cover to cover, but it's very useful. (Realistically, though, an LLM is probably good enough to explain basic concepts and/or help you pick parts these days.)
4) Build a toy robot with parts you printed (or purchased) and parts from the electronics kit.
5) Once you've built the toy robot, make something bigger! (or the existing one better!)
6) Optional: Find someone to buy your toy robot so you can have the funds to design and build your next one.
I'm reading this and kind of stuck on the 4th. I have a printer though not much of 3D designer. How do one get 3D models for parts that is suitable with SparkFun electronics?
For electronics, all you really need to get started is an Arduino, 3 hobby servos, and a breadboard and wires. The first robot I sold was basically just that. And the physical parts were Lego-Technic compatible laser-cut (later 3D printed) beams. (https://bitbeam.org/, https://www.thingiverse.com/thing:11747)
Start making your own "lego" then go from there. This idea can get you pretty far --> https://bitbeam.cc/en/
This was basis of the robotics company (Tapster) that I started and have been running for over 10 years now: https://www.flickr.com/photos/68386867@N05/7855484076/
Adafruit is your friend. Get one of their feather boards, an imu breakout, motor controller and then a simple robot chassis + motors from Amazon. Code in circuit python and save yourself the build chain and debug hell that is traditional embedded programming. Circuitpython / micropython is great, well supported, and makes embedded programming more fun. You’ll encounter the haters see it as training wheels but trust me, it’s great.
Edit: you could take a more top down approach and get like an ardupilot, use it in rover mode, and just really learn how to configure and use it to its full potential which is pretty far out there. There’s also a lua scripting capability last time I checked.
It's not more accessible than ever. If you want to make it in robotics, you're going to have to read research papers and preferably have attended as many robotics related courses during university as possible. The hobbyist scene is big, but the vast majority of robots are basically fancy toys and almost no one ever goes beyond simple PID. The problem is that robotics is clustered around industrial robots and academia with nothing in-between. Unless you have the necessary background, you will most likely be stuck scraping the surface simply because you're not aware of the most recent developments in those areas.
If you want to understand how it works, take first Stanford's CS223A and then MIT's 6.832 Underactuated Robotics courses. They have lectures online as well. Udacity's Self-driving Car Nanodegree might be a good idea after those two.
From the electronics side, the path towards control theory is a lot of math (signals and systems, Fourier transforms, transfer functions, feedback and oscillations, compensation circuits) ultimately leading up to the student solving the inverted pendulum problem sometimes in early Masters degree region or maybe the advanced student Bachelor's degree.
I'm not entirely sure how to make that more 'accessible'. It's like, spend the next 5 years of your life mastering difficult math and electronics so that the sensors can be integrated into feedback that stabilizes a motor system.
I guess you can cheat and use servos for a lot of this (where an EE already solved many feedback loop issues). But if you ever need to build your own sensor+motor solution you'd get stuck if you didn't know the math.
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Making simple controls without relying upon feedback sensors is likely the goal, you can do a lot with that. But then do your best to avoid the Masters level demons that plague this problem set.
Maybe learn PID controller theory and if that isn't enough for your problems, give up and try a different design. PID is simple enough that you won't need years of math to learn, but it's very adhoc to configure and not always the best methodology to use.
Better than nothing though.
I've just started this journey. I always wanted to get into electronics and robotics, but instead went the software route. I've picked up an Arduino and microbit over the years, but they sit collecting dust.
It may sound silly, but I asked Gemini to recommend a learning plan and it came up with a detailed plan along with time estimates in months. The first step is reading and going through all the exercises in Make Electronics (third edition) which is very hands on.
When I took the robotics course in grad school, we spent so much time on inverse kinematics and other complex math. It was pretty intense and gave me the perception that robotics was pretty difficult.
Yet, today, people easily build simple robots using a few rc servos and an Arduino. Somehow kinematics is not really essential if you just want to build simple robotic toys. The pedagogy of robotics courses could have been so much better...
Many robotics tasks can be solved by linear motors and grippers. Not everybody needs to make 6 DoF arms. Nor they need machine-learning enhanced optimal control. Grad schools prepare you for the basics of the hardest possible systems.
On the engineering side the number of difficult problems with robotics is enormous. Even the simplest systems will fail pretty badly outside lab. No two robots will work the same. As a grad student those are the things you learn on top of IK at work. So if you get employed for designing actual 6+ DoF systems and missing the theoretical stuff you'll be way behind.
However, for self teaching and hobby stuff, just making a simple robot work reliably is still a difficult task with lots of learning potential. It may not cover complex arms but you may actually gain knowledge to solve the engineering part of the problems which is a huge boost for theories.
Don't do a degree or two like I did. Just build shit, get yourself a 3D printer and some electronics, and again just build shit.
The only maths you'll need at the beginning is basic control engineering (PID Loops), forward/inverse kinematics and Extended Kalman Filtering. The only other thing is maybe V=IR, anything else and you're just placating some professor's ego.
It's not that hard to get started! I make robots like this (that one's just to enter the wiring stage) using alu extrusion beams, some 3D printing, off-the-shelf servos and SBCs:
https://i.imgur.com/9YIHT9P.jpeg
Modern SBCs are decently powerful and run for long enough off a standard drone LiPo pack that you can fairly easily build yourself a solid little platform to learn and experiment with different controller approaches. Stereo cams, LiDAR modules, etc. are also readily available at a quality level that is decent enough.
You'll quickly realize the amount of work needed to bring any of the more advanced approaches to a productization level, but a "I implemented enough of this to get the principle" mini-Boston-Dynamics is in reach of the hobbyist.
In fact, the programming craft aspect of all of this is relatively simple. Basic implementations are typically not architecturally complex or a lot of sloc. You'll find that it's more about learning some control theory, and it'll also get you into machine learning.
Your workbench is so much cleaner than mine!
It's a small inner-city apartment and it's my little corner in the shared office room with the better half, that motivates me to keep it tidy :)
A common beginner project is to build a line following robot. You get to learn a bit about electronics, microcontroller programming, sensors, actuators, etc. e.g. https://projecthub.arduino.cc/lee_curiosity/building-a-line-...
Robotics is a large multidisciplinary area, comprising of parts of ME, EE, and CS fields. Before you go down a particular path, it may be good to step back, and note down things which you actually enjoy doing, and how they might relate to one or more of these fields. After all the drama wears off and you are up late working on something .. it's important to enjoy what you are doing. Not just trying to catch some hype about the next big thing or the tech giants or AI or whatever (or something your friends or parents told you).
The top comment refers to a course around a small mobile robot. Maybe you could go through this, and try to build a bicycle which would balance itself and drive a 100 yards in an empty, safe parking lot. That will certainly involve ME, EE, and CS! Who knows where that might lead?
It’s incredibly easy but for some reason seems hard
But no matter what you need an actual physical robot I have never once seen anyone actually transition into robotics without them having made the commitment of spending $100s or $1000s on a capable robot. Very capable robots are in that range at this point.
1.Figure out what you want the robot to do. This is the hardest part, cause it requires constraining your desires considerably
2. Figure out how you want to make it do that. Do you want a deterministic robot? Do you want a robot that uses inference?
3. Then buy the robot that can do the physical action. If your task is to move groceries from your car into the house, you have much different requirements than if its a linear actuator flipping a static switch
4. Choose your robotic actuation path: Dedicated embedded controller (FPGA, PLC), controller coupled with another switch, autopilot etc…
Test, iterate, test….
A good starting point is learning to use ROS https://ros.org/. Once you learn ROS you can interact with/use a wide variety of robots. Robotics is a fairly multidisciplinary field though, so it really depends on what area of robotics you are interested in.
There's 3 core parts:
- Electronics (batteries, resistors, capacitors, etc) - Robotic hardware (motors, sensors, microcontrollers, etc) - Software
The electronics learning is always going to apply to start there if you need to, then depending on your goals the hardware and software will vary.
For simple DIY projects I'd start with getting an Arduino or Arduino compatible board and just play around with building things with sensors, LEDs, motors, etc. You'll find lots of kits and resources online for simple Arduino projects.
More complex projects are probably going to need to be Linux-based (AI, machine vision, etc). In which case you might want to look at building something with a mini PC, Raspberry Pi, NVIDIA Jetson.
These days robotics is super accessible, but can cost a bit depending on what you want to do... That said, most of the time you'll find there are cheap ways to build POCs to validate your ideas first.
In all honesty I’d try and model a 2d 3-link arm in software with forward and inverse kinematics. Then I’d model the inertia of the bars, and model DC motors to apply a torque to the bar interconnects. I’d then model PID controllers for each motor to smoothly move the arm. I’d then move to 3D. Once the physics is modelled you’ll find speccing the motors, solidworks, motor drivers, and MCUs relatively straightforward if you have some basics in electronics.
The fundamentals of robotics is in the math; think control theory. Don’t over emphasize the surface level like ROS, arduinos, and Lego kits. Those are implementation details
Snoozefest for anyone looking to get hands-on. Arduino kits can be had for $50 and then 50 lines of c++ will have basic forward kinematics on a ~10 inch arm you can play with in the real world.
Really? I’d have thought 50 lines of arduino would’ve been a snooze fest for hackernews
I’ve been playing a bit with toy robots and vision models and I can’t shake the sense that somebody has got to be close to simplifying the control game with high fps cameras. Why are there so many systems to control motors and ground positioning … shouldn’t it all be cameras on the arm figuring out if the motors have positioned the arm correctly and updating to fix?
This is obviously naive and computationally wasteful but I really want to see vision first rebuilds of most control and feedback systems.
Biological analogies are always a bit dodgy, but biology hints that this doesn't work very well. Vision is important, particularly for path planning, but the immediate feedback of proprioception and touch is more important for stability. Think of how hard it is to walk normally when your leg has fallen asleep --- your visual cues remain unchanged, but you lose the immediate feedback loop from your leg. You can do it, but your gait is very unnatural and inefficient.
The best way to learn is just by running small experiments and being curious about the field.
Just a few weeks ago, along with my partner i started this Sunday experiment of building and learning robotics as a software engineer.
We ordered a one hand robotic arm with orin nvidia gpu to start running experiments.
to commit and make it a habit, we also started documenting our learnings and experience.. if this motivates you you can check it out here - https://youtu.be/pAwkl6zd0ws
I was just digging out this Roomba I modded with a Raspberry Pi and camera. I think the cost of that setup was like $40. I meant to get my kids into robotics but they lost interest ... so this cool platform is still sitting around...
Everyone is jumping the gun here. You just haven't told us enough.
How much time do you have? How much do you know about hardware and software? What do you want to do? How much money do you want to invest? What do you want to learn?
The path forward changes entirely depending on the answers to these questions.
Has anybody tried Crunch Lab's HackPack? It seems it could be quite well suited for this purpose -- they claim to make it straight forward to go beyond the kit, and they've certainly taken some of the right steps in that direction.
I tried it. First kit was speced with cheap parts that didn’t really work. Got a replacement kit - same thing. Overall a really disappointing experience. I cancelled and bought a 3D printer, which has been great fun.
Edit - fixed autocorrect
A really top-tier robotics engineer is going to be a generalist across mechanical, electrical, and several software domains, and then also a specialist, deep expert in one or two of those. So I'd recommend doing a bit of everything then picking a specialty to learn in depth. Build a really simple kit robot and then program it to do simple stuff using ROS. Write a few ROS nodes from scratch to do something simple, things that existing ROS nodes already do. Then learn why the STL ROS options are (most likely) better than yours.
I strongly recommend taking the generalist approach. It makes you a much better engineer in the long run. I had a friend call me up enraged one day. He got woken up at 1am and ordered to drive across the state to get a site back up and running because his hardware was broken and the very expensive software team was sitting around wasting their time. So he got to the site at three or four AM and found that the room full of software engineers, three PhDs among them, didn't understand that BOTH of the battery terminals needed to be connected. Yes, batteries in fact have a positive and a negative. And these people were each getting paid twice as much as him. He left that company and became hardware leadership at a much better company, thank goodness. My point is, super-specializing in the most profitable hyper-niche right off the bat is going to make you a very mediocre robotics engineer who might be successful in the short term, but might find yourself unemployed in a few years when we find a better modality to replace your hyper-niche. Specialists win the sprints, generalists win the marathons.
This guy makes cool stuff and releases the source code.
https://www.youtube.com/@jamesbruton
No one here mentioned to get a 3D printer but get a 3D Printer asap.
Yes, if you can get okay at printing, the friction from idea to implementation dissolves quite a bit. If you're building POCs, it doesn't matter than this gear won't work be durable or that chassis is ugly. Having it in hand for pennies means you'll actually build your idea. It's much like using packages in software. Maybe they aren't perfect fits for what you're building, but they get you close enough. You can refine later once you know the system works. The gap between idea and implementation is so dramatically reduced that it doesn't matter.
Right, so instead of getting involved with the basics or foundations of robotics, the OP should spend a lot of time and money investing in a 3D printer, learning the nuances of 3D printing, and ... for what exactly?
Thanks for sharing knowledge about robots, maybe I can get my hands on one sometime!
Honestly, and I feel like a promoter… but get either a hackpack from Mark Rober or as otherwise mentioned, mindstorms from LEGO.
Crunch labs: https://www.crunchlabs.com/
As someone in the industry (I literally can call myself a Robot Master having a Masters Degree in Robotics), these simple “kid kits” are phenomenal. When you first start out, the hardest part is knowing the hardware is actually going to do what you tell it to do. Simplifying the mechanical engineering/electrical engineering so you can immediately create real world actions makes a huge difference in giving you motivation to keep going.
Once you have the basics in place and you understand mechanisms, sensors, and some algorithms, you can move on to other parts of robotics.
However, keep in mind robotics is really about system thinking… you have to understand trades between sensing, thinking, and acting. But most importantly you have to remember you are dealing with the real world… you can’t as easily write a unit test and know that a particular actuator will behave exactly the same way every time.
Depending on your goals, micromouse could be a good starting point as well. Look up to veritasium video if you want to get inspired.
There are many ways to start with a more academic knowledge of robotics. Courses, ROS, Programs etc. Just picking one is a fine start and you will learn something, but you may not have fun or appreciate the context for what you are learning, which makes it hard to care.
It also depends on what you're trying to learn. Programming? control? electronics? mechanism design? There are many different aspects that require their own expertise. I personally think of a roboticist as someone that can be functional in all the disciplines and bring it all together. Some one that can build a robot from scratch.
This advice is targeted towards someone starting in robotics with an emphasis on building a totally custom robot. You are doing the whole thing from scratch, no kit. (kits are super useful, but I personally like building everything and making hardware that works for me). In my eyes, if you haven't built it in hardware, it probably isn't a robot.
As a research roboticist, my best advice is forget Learning it all up front and just start building. You will probably have strengths and weaknesses, but robotics is a very multi-disciplinary problem and at the start, requires some head banging in what we like to call integration hell. Just Trying to build something does a couple things. It gets you acquainted with the interaction of all aspects (mechanical, electrical, software) of a robot and how they interact. Most importantly it gives you context for sll the things you learn later on. Build something, come across a problem, and google/brute force your way to a solution. You will stumble across context relevant resources and lessons in the moment. Especially at the start, a more "formal" education is too broad and comprehensive for the curious roboticist.
My simple advice is to just come up with something simple and SEND IT!
For mechanical - Onshape for 3D design (free tier) and a bambu A1 mini 3d printer can get you building anything you want for <$400. A couple nights of CAD tutorials will get you started. Hell you can even start with cardboard and hot glue if this is cost/time prohibitive.
For electronics - Browse www.adafruit.com or www.sparkfun.com for sensors and microcontroller boards. They both support QWICC connections which makes getting sensors plugged in and running super easy for a beginner. For computation and control a basic Arduino Uno or one of the adafruit feathers will do just fine. Don't get caught up in the internet debate on what the best microcontroller/single board computer is. The best robot is one that works and it is VERY easy to get in over your head in this realm and fall into the premature optimization track. Better to get something working that under performs than to never build at all.
For software - Most lower level robotics uses c++, which I think scares people. It is mostly because it is one level above hardware. Arduino/common libraries take care of all the hard stuff and you don’t have to worry about large scale things like garbage collection, memory leaks, or efficient code off the bat. The websites above have libraries, examples, and tutorials for every sensor. Even a non programmer type can smush the example code together in a functional way and get something up and running.
As you try to build you will learn and get more complicated. Robotics is so vast and large its best to focus on learning the skill you need at the time. But my main advice is just go build the thing and the learning resources/skills will present themselves when they are needed. Otherwise it is just too much to take a more planned approach.
Build your own (small, diy) robot. Practical applications are the primary method of learning imo.
Great, you know what you want to make. Go ahead, and do it. Look at projects previous folks have done, see how then can be adapted for your need. If you are interested in getting this One Amazing Thing working, great! You have the motivation and cranking through what you'll need to lean to succeed will be possible.
IF, on the other hand, you want to make 1e6 of these things ("tech giants seems to capture most of the conversation")-- that a completely different story. You're going to need a skilled team, ideally one that has been to a rodeo before. I can't help you there.
But if you're building one, for fun --- Just DO It. Ask friendly robotics club members when you get stuck. IF your problem is particularly and singularly unique, then whatever domain that entails, you will need to master; that's your Secret Sauce.
Ivan Sutherland, who was Thesis Advisor to CMU's first Robotics Institute PhD said something to the effect that after 4 years of a Robotics PhD program, you end up with the ability to solder and attach connectors with a high degree of confidence.
A True Roboticists requires deep knowledge in mathematics, software engineering, mechanical engineering, manufacturing small lots, reliability engineering, materials engineering, data collection & graphical evaluation methodologies..... What one might call a Systems Engineer's handbag. It also helps to be inspired by the wonders of nature that biology affords us.
The details? eh, they change. Whether you used some hot cpu, some hot language, some hot OS --- Marc Raibert's hopping & jumping robots used C and BSD4.3 Unix, with the kernel locks cleaned up (reduced) so a 1 kHz kernel interrupt stream could be supported on a 1 MIPS machine (Vax 780). Timesharing was never stopped, but the kernel did get quite a large percentage of CPU cycles.
I'll repeat: Just do it. Start. Move forward. The project will teach you the questions you must ask.
I knew Dean Sutherland at CMU, nice guy. And dad was right. Turns out an advanced grad-student software group had brought me in (back in 2004) because their grad students couldn't build reliable software for the real world, and their military "research partners" were getting rather p.o.'d. But I'm a non-degreed Mechatronics Systems Engineer, in the truest sense of the word. I'm old enough to predate software engineering programs. I learned robotics and automation because I was curious, it fueled my ADD, and I kept at it... in the beginning I used plug-in cards for the IBM PC, but I knew basic electronics as a hobby (ham radio, telephonics, heathkit, etc.) and I devoured books. Anything I could get my hands on. Especially Byte magazine and Steve Ciarcia's Circuit Cellar columns. So get copies of Forest Mims III stuff, and get an arduino or raspberry pi (you can even get/run Codesys on a pi, to learn PLC stuff) and get magazine issues/books from Make: and watch lots of youtube from ElectroBoom and AvE and get your hands dirty. Remember, you can be skilled at robotics without building Optimus. Currently I'm building and programming high speed mail handling equipment. Not sexy, but it pays the bills and fuels my dopamine. It's all servomotors and sensors and decision logic. And challenging too, paper's moving at 1/8" per millisecond at mid-speeds, you need to be an efficient coder and pre-optimizing your logic, and it's all state machines, all the way down. Good luck. I make bank, but I'm driven in a thousand directions and I push and I try and while I may be wrong 70% of the time, that would get me into the allstar game if it was baseball! Never give up, and never surrender! LOL
Check out isaac sim from nvidia
I love to create an robotic arm like cyberpunk 2077
(Ask HN:)
Noted not just for pedantry but you may get more attention.
Related: what about Embedded Systems?
Thanks. Very Helpful!
K-Scale Labs: Open-source humanoid robots, built for developers
- https://www.kscale.dev - https://news.ycombinator.com/item?id=44023680
A kernel developer plays with Home Assistant
- Part 1: https://lwn.net/SubscriberLink/1017720/7155ecb9602e9ef2/ - Part 2: https://lwn.net/SubscriberLink/1017945/93d12d28178b372e/ - https://news.ycombinator.com/item?id=44011381
Dutch ingenuity: A brainless soft robot running on air
- https://arstechnica.com/science/2025/05/dutch-scientists-bui... - https://news.ycombinator.com/item?id=43972689
Gemini Robotics
- https://deepmind.google/discover/blog/gemini-robotics-brings... - https://news.ycombinator.com/item?id=43344082
Morphing robot turns challenging terrain to its advantage
- https://actu.epfl.ch/news/morphing-robot-turns-challenging-t... - https://news.ycombinator.com/item?id=43194234
RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning (2023)
- https://kzakka.com/robopianist/#demo - https://news.ycombinator.com/item?id=43192751
Ask HN: Best way to learn robotics with a 10 year old?
- https://news.ycombinator.com/item?id=41070703
DARPA project reveals one person can control dozens of robots
- https://spectrum.ieee.org/darpa-robot - https://news.ycombinator.com/item?id=43209358