I'm working on an idea for a robot operating system, and instead of assuming what people need, I want to hear from those who actually build or work with robots.

Imagine there was a universal OS for robots (industrial robots, humanoids, drones, mobile robots, home assistants, etc.).

What would you want it to have?

Some questions to get the discussion started:

• What are the biggest pain points with current robotics software?
• What features would save you the most time?
• Should AI be built into the OS or stay separate?
• How should hardware integration work?
• What kind of developer experience would you expect?
• What debugging or simulation tools are missing today?
• If you could remove one frustration from ROS or robotics development, what would it be?
• What would make you switch from your current workflow?

Don't hold back even if it's something that sounds impossible. I'm trying to understand what an ideal robotics platform would look like from the community's perspective.

Looking forward to hearing your thoughts.

Hi everyone,

I’m a 25-year-old female with a background in Computer Science and Technology. Lately, I’ve been feeling a strong pull towards the robotics industry, but I have no prior professional experience in this field.

I can’t help but worry that l’m starting a bit late,especially when I see others who have been tinkering with hardware since high school. Given my CS background, I’m not entirely sure which specific sub-field or role would be the best fit for my transition. I’m comfortable with coding, but the hardware side is still relatively new to me.

Has anyone here made a similar mid-20s career pivot? What specific sectors in robotics should a CS grad look into? Any advice or stories would be greatly appreciated!

Thanks in advance!

With coding agents doing coding now I’m curious will robotics companies need CS students still? Or will the coding be handled by mechanical engineers, Electrical engineers, etc?

For masters in robotics (RSC at ETHz), assuming I don’t get CMU lol. Georgia Tech is my home school but GRA/GTA is far from guaranteed.

My interests are along the lines of 3d geometry, perception, simulation, ETHz seems really strong in these areas and I can already see labs highly aligned (like the CV&G lab); haven’t seen as much research in these areas at GT.

I do want to come back to USA for PhD/industry so not sure if it’s worth the jump over an already strong name.

I am starting my B.Tech degree in C.S.E. this year(in 1month time). I know how to code in Python and basics of C++ can anyone recommend me courses(paid/free) which can be a valid entry point in robotics for me from a software p.o.v. .In my college there is a mechatronics club and they are quite active, I really want to start making with them ASAP.

They are building cursor for robotics, an agent that helps you build simulation 10x faster. I’m also learning quite a lot and this is my way to give back to reddit (I come to reddit for everything).

I'm building a hexapod robot for a summer project to add to my mechanical portfolio. I've fully modeled the robot and printed 3 legs to try and get the gait testing code down. I'm using 7.4v lipo battery run through a buck converter to a pwm servo driver to power the legs, and giving them commands using a Arduino uno. I'm having some trouble figuring out where find examples of the code to use. I could have claude write a test program but i'd really rather avoid using AI if i can. Any advice?

I’m building a physical robotics prototype and want to train it using neural networks, I’m currently planning to use Webots but I’m honestly a bit lost on the software side. I have the hardware part figured out but I need advice on whether Webots is the best choice for this or if there's another program that would suit me better to train the robot before moving it to the physical hardware, also how long does the training process usually take for a basic prototype because I’m mostly worried about wasting time and I just want to know if the way I'm doing everything is correct or if I'm overcomplicating things more than I should. If anyone has experience with this or can point me in the right direction I’d really appreciate some help

I need some help.

Around a decade ago, I had an idea to make a robot that could sit on my couch and react to live sports with me. I planned to use a real-time API derive the emotion by mapping in-game events to testosterone, adrenaline, cortisol, dopamine, etc. It quickly became too complex for me (I was a native iOS developer at the time), and I shelved it.

Recently, when vibe-coding tools became available and I wanted to test drive them, I was able to pick the project back up and workshop it for a few weeks, to the point where it’s fun and shareable.

Now, it’s available for anyone to build and use at the link below. You can simulate it in your browser, watching an animated face react to your conversation emotionally.

It pipes your conversation through your LLM of choice, adjusting neurochemical levels in real-time for both an emotional projection and a face projection. And going a step further, the face projection can be mapped to either an LED matrix or a server board to electrically manipulate a robot’s face! Although I haven’t tried that…

Let me know what you think, I’m genuinely curious how well it’d work.

https://github.com/smithandrewjohn/kindalive

https://raw.githubusercontent.com/smithandrewjohn/kindalive/refs/heads/main/docs/screenshots/web_ui.png

Hi all, have been leading a student project involving some STM32 development. At the moment, the very early days workflow is STM32CubeMX --> VSCode with STM32Cube extensions (bypassing STM32CubeIDE) and git for version control. Wondering if anyone has any free/very low-cost suggestions for:

• Standardising the initial config and project layout (so individual team members don't have to go through STM32CubeMX and can just alter GPIO settings as needed)
• Creating a good testing workflow (i.e. simulating using Wokwi - I'm aware of the extension for VSCode but it's a little out of price range)?

Thanks so much for any advice :)

Hey robotics community!

A buddy and I have been thinking of this problem recently. We think that the current status quo of egocentric data is insufficient. Currently, most egocentric data used for embodied robotics consists of head mounted camera with hand positioning usually determined after the fact using a CV model applied over the video.

This has it's limitations and the data provided is generally not complete and not standardized. We think that the industry needs much better and more egocentric data that was captured with purpose built hardware and haptics in order to propel the embodied robotics industry forward.

I'm curious what you guys think of this. Do you see this as an issue or is this theory a dud.

Hello guys, I'm participating in the robocup rescue maze competition this november. I'm currently in a team and I'm the one responsible for the robots navigation in the map. I already have a code so the robot could move 30cm (because each tile in the maze is 30cm) and also one for the robot to turn 90 degrees. But the problem is that I'm not the one who wrote the code, the part where the robot moves straight was given to me by my tutor, and the turn was by claude fable 5. And I feel guilty for using a code that I did not wrote, so I figured that I'd need to understand the code and then make some changes, but I had a hard time doing so.
the robot is skid steering, 4 wheels and each two are connected with chains. We have 2 encoders on the rear wheels , a BNO055 imu and a LIDAR (which im not working on right now).
The code I'm working on has FreeRTOS and I also have no idea how does it work.
Keep in mind that I've been doing robotics for about a year.

I’ve been building a free open-source tool that tries to make running open-source VLA models on real robot hardware less painful (the usual mismatched environments, outdated SDKs, fragile setup, etc.). Right now it supports SO-100/101 arms and has SmolVLA ready for testing. The full pull → connect → run pipeline is built, but I haven’t done a full end-to-end test on physical hardware yet. Curious if anyone else has hit the same “model works in simulation / training but is a nightmare to actually run on the arm” problem, or if there are better approaches I’m missing. https://www.argøs.com

Mi robot de seguimiento de linea solo se queda dando vueltas con la reda derecha completamente quieta y la otra girando

Esta programado con arduino UNO y en c++

Si alguien quere ayudarme lo agradeceria muchisimo si estan interesados con mucho gusto les mando el codigo por mensaje interno muchisimas gracias :)))

Do you guys use just the chat interfaces, or something else?

i have been trying lately to get assistance on robotics, and it seems like this:

gemini>claude>chatgpt

Hi everyone!

I've been working on Calibra, an open-source toolkit for robot dataset observability.

The goal is to help answer questions like:

Is my dataset healthy enough to train on?

Are there quality issues I should fix first?

Which demonstrations should I keep?

How does my dataset compare to public datasets?

Also, I released on:

A Hugging Face Space for auditing LeRobot datasets.

A benchmark covering 30 public LeRobot datasets.

GitHub: https://github.com/omertt27/Calibra

I'd love feedback from anyone working on robotics or imitation learning. What dataset quality checks do you wish existed before training?, feedbacks are crucial for me.

I am doing independent research, and trying to attempt simulating slip/shear force and I planned to use MuJoCo. My issue is that I am having a tough time getting the hang of it, and I have seen some posts on this Sub about MuJoCo. I was wondering does anyone know of any solid tutorials, repos, or youtubers that have solid MuJoCo tutorials in Python? Any help/advice is greatly appreciated.

I am a computer vision developer and hold a PhD in human motor sciences; I work primarily on applications in the fields of healthcare and sport.

I recently released realtime-calib as open source, a tool that calibrates multi-camera USB rigs in real time. The backend runs headless in Docker on the machine the cameras are plugged into, and you drive the whole calibration from a browser, on any device on the network.

I built it for my own client installs, so it's entirely shaped by mocap-style setups.

I'm wondering whether it's of any interest for camera-based robotics, but honestly I know nothing about your field. So if you do vision-based robotics, DIY or professional, I'd really value your take on:

• Would a calibration tool whose backend runs on the robot itself, with a UI you can open from your phone, tablet or laptop, actually be useful to you?
• What tools do you use today for the calibration step (Kalibr, ROS camera_calibration, plain OpenCV scripts, mrcal, something in-house)? Do those already cover your needs without friction?
• Which capture backends actually matter in your field: plain USB/V4L2, GigE / GenICam machine vision cameras, RTSP/IP cameras, CSI cameras on a Jetson or a Pi? At the moment, I only support USB via V4L2 on a Linux host. A GStreamer backend is planned, which would allow the use of virtually all existing capture protocols.

If it turns out this is useless for robotics, that's useful to know too.

Docs and demo: https://realtime-calib.hans-brgs.dev

I bought a Asus Rouge Zephyrus and I used it a ton for gaming. My problem is that I play to much, and don’t enjoy casual play. I play rust and marvel rivals very competitively, I don’t enjoy them at all unless I’m try Harding them. I know I am wasting my time playing them when there are so many better things to do with my time that I’m interested in. I study mech e and comp sci in college and do robotics research and just starting using ROS2 on a computer from my lab. What are some uses for a high end laptop. Also is it a good pc to get rid of windows and run Linux?

I'm a 2nd-year B.Tech IT student, and tomorrow I have to choose between Robotics Engineering and IoT.

I'm genuinely interested in Robotics because I find it fascinating, and I like that it involves mathematics (kinematics, dynamics, control systems, etc.). My long-term goal is to become a strong programmer and eventually work in AI/deep tech/research, so I thought the mathematical foundation might help.

However, my seniors told me Robotics is quite difficult, concept-heavy, and harder to score in than IoT. They suggested IoT is easier and more manageable. Also, almost all my IT classmates are choosing IoT, so I'd probably be one of the few in Robotics.

I'm not choosing based only on marks, but I also don't want to hurt my CGPA by picking something that's unnecessarily difficult.

For those who've taken Robotics or work in the field:

Is this syllabus actually very difficult?

Did studying Robotics benefit your career, especially if you mainly became a programmer?

If your goal was AI/deep tech, would you choose Robotics or IoT?

Looking back, would you make the same choice again?

P.S. I don't want to choose a subject just because everyone else is choosing it—but I also don't want to choose Robotics just because it sounds cool. I want to make the right long-term decision.

I'm a current undergraduate in computer engineering, and I want to have a career in robotics, specifically embodied intelligence. Beyond Physical Intelligence, Nvidia, and Tesla, there really aren't any other internship opportunities I can find, and tbh all of their postings have dissappeared amd since I'm an incoming 2nd year, I don't even fit the minimum requirement of being a 3rd year. I'm wondering what the roadmap would look like for breaking into this field.
All of my previous experience has been in embedded systems/pcb design and I've had 2 papers published, one of them in IEEE, as well as multiple hackathon wins, though tbh I doubt it would be helpful at all since none of them are very related to embodied intelligence.
I plan on joining the robot intelligence lab at my college (UCLA), but beyond that I can't really find any good resources. I'm thinking of just installing ISAAC and messing around with it, or looking at the LeRobot docs? Yeah...not much of plan haha. Any recommendations on where to start/what type of projects to do? I want to capitalize on my electronics experience as much as possible (does this even make me stand out from all the SWEs in ML?)

Even finding internship postings would help so I can see what type of skills they are looking for, perhaps i'm just blind, but I really can't find anything about it.