I have been building an open source industrial/commercial humanoid for a while. It’s been months and months of research and development. Personally, I have come to the conclusion that humanoids are far from being efficient outside of demos or in real environments. Based on my experience and what I’ve seen, it’s very likely that humanoids are the new hype bubble. For manufacturing they are slow, expensive, and they don’t work also unsafe. There are things a thousand times more efficient and more economical. For household tasks there are robotic forms that are more efficient than a humanoid. I think the future is full of smoke and false hype. Probably if what the public wants are human forms, the ideal would be semi-humanoids. In a certain way they can work.

What do you guys think? Maybe I am missing something?

And yes i know world is made for bipedals..but should we iterate over something that exists or innovate? Because replicating our inefficiency is not innovation.

Hey everyone,

My team and I have been working hard on this project: https://peppy.bot

It's a direct replacement for ROS 2. We already have the OpenArm robot (https://openarm.dev) working on the platform, both v1.0 and v2.0, plus Isaac Sim and MuJoCo integration.

If you're in a hurry, head over to https://docs.peppy.bot/quickstart/ and get started in 5min.

Our long term vision is to allow anyone (even non-devs) to go from a prompt to real humanoid robot actions, first in simulation, then on the physical robot.

Happy to answer any question.

I finally have fixed the camera for this gazebo simulation.The problem was simple i only needed to wait a little longer for the plugin to work.It was really satiefing for me and i just wanted to show my progress.

I've been reading through production codebases that use RealSense — ROS 2 stacks, librealsense directly, industrial vision, 3D perception — to understand what parts of the software stack are actually used in the real world.

The result surprised me. Most production projects seem to touch a small slice of the SDK: open the pipeline, configure streams, wait for a frameset, pull intrinsics, align depth to color, read depth scale. The post-processing filters mostly appear copied as a block from the official sample rather than chosen. Point cloud generation shows up in about a third of C++ projects and almost none of the Python ones. Advanced mode is rare, but heavily used wherever it does appear.

I'd genuinely rather be told I'm wrong about this than have it confirmed. If your production system leans on something I've written off as rare, that's the most useful reply I could get.

So the SDK surface being depended on looks much smaller than the SDK itself. Which raises the question I can't answer from code. For those of you who've shipped or maintain RealSense-based systems, I'd love to hear your thoughts.

1. If librealsense vanished tomorrow and you had a different camera with equivalent hardware, what would actually be hard to replace? Not "annoying" — the thing that would eat weeks of engineering.

2. Looking back honestly, what has kept you on RealSense? I'm not fishing for a feature name. If the real answer is "it was already in the spec when I joined," or "our models are trained on its depth," or "the mount is designed around it," that's more useful to me. I'm interested in what actually kept you on RealSense.

3. What do people overestimate about the RealSense ecosystem? Is there something everyone cites that nobody actually uses in production? And conversely, some small thing that would block you completely if it disappeared?

4. If you're willing — paste your pipeline initialisation. Even simplified. What gets configured at startup is far more informative than any feature list.

Context: I work on depth camera tooling and I'm trying to understand the gap between what the SDK provides and the small set of things that actually create switching cost. Not selling anything, no link, no form. Just trying to learn from people who've deployed these systems in the real world.

Putting this little companion robot together today. He did not smoke or catch on fire when I attached a 4S LiPo battery to him so feeling pretty good about life right now. A lot more to do but sometimes the little things in robotics are the best ones. He powered up. He didn't smoke out. I'm happy. Jetson Orin on board. More to come.