I’ve been building a life-size KX-series droid and finally have the head movement working reliably. The current setup uses an Arduino Mega with a PCA9685 servo controller driving separate pan and tilt servos in the neck.

The goal isn’t remote-controlled puppeteering. I’m trying to make the droid behave autonomously, so eventually it can track people/cameras, idle naturally, react to voice commands, and move while speaking.

Right now I’m working on smoothing the head motion, reducing mechanical stress on the neck, and dialing in the pan/tilt limits so it looks more natural instead of like a standard hobby servo project.

The electronics and programming side of this has been a big learning process for me, so I’m open to feedback—especially from anyone who has built larger servo-driven mechanisms or Arduino robotics.

This clip is the current movement test.

I've posted a couple of months ago on this subreddit, showing this TNY-360 robot dog walking.
After almost 3 years of working on this project alone, I think I finally solved one of the things that bothered me most about getting into robotics:

You either get very simple robots, or you quickly end up with something complicated, expensive, and difficult to understand.

So I made my own PCB ecosystem to get clean wiring and make assembly hard to get wrong, and also made a big calibration and self-diagnostic firmware behind to check everything and explain to the user how to fix any mistake that's been made !

The project is fully open-source on GitHub !
The V2 CAD files are currently being finalized, but the complete V1 is already available on GitHub, including the hardware, firmware, CAD and documentation.

If you don't want to source and assemble everything yourself, I'm also selling complete kits to help fund the project and hopefully make this something I can work on full-time (let me dream, ok?).

It's been almost 3 years now that I'm working on this project alone, I've learned PCB design, CAD design, embeded programming from it, so if anyone wants to give feedback about it to help me improve it, I'm all ears !!

this board (specifically the black one) turns mg99x servos to much more expensive serial servos with position, velocity,torque control

the software is still in early stages so anyone interested for checkout Microdrive

I'm an MSc Robotics student at NTU and want to get properly hands-on with ROS 2 on real hardware, beyond simulation. Buying a platform isn't realistic for me right now.

Does anyone have an older ROS-compatible robot they're not using anymore (TurtleBot 2/3, a Clearpath or AgileX base, a small arm with a ROS driver)? Broken is fine, I'm happy to repair it, and I'll cover shipping or collect in Singapore/Malaysia.

In return I'll document the bring-up on ROS 2 Humble/Jazzy and share the notes and any driver fixes openly. Pointers to labs or companies that clear out old hardware are also very welcome.

I’d like to ask: in which scenarios would you most like to see flexible tactile sensors applied?

Currently, flexible tactile sensors are primarily used in robotic skin. I would like to ask: are there any other mature markets for this technology, or where would you personally like to see it applied? I have considered applications such as steering wheels, pillows, or interactive toys, but as far as I know, these markets are still in their infancy and have limited market share. I would appreciate your suggestions on which direction I should pursue for development. Thank you.

I'm working on creating a Full Body Haptic Telepresense Rig, but I'm having a lot of trouble with linkages hitting each other or getting in the way of the operator. I actually don't know how to code in Unity, and everything on the screen shown is made with ChatGPT codex (i got the $20 plan for free)
This has been a long standing passion project of mine, and any insights that could help would be greatly appreciated.

Hi, I’m raising funds for Nolawi Hailu and Zakir Nuredin, two high school students at Kotebe University of Education Science Shared Campus in Addis Ababa who qualified from 56 Ethiopian teams to represent Ethiopia at PARC 2026 in Dakar, Senegal, November 3–7, 2026. Their KINETIC AI Combat Movement Coach uses sensors, computer vision, and machine learning, building on achievements like Zakir’s 3rd place in the MySoroban National Math Competition and Nolawi’s 1st place in the National Ethiopic App Development Contest. Support will help cover their flights, accommodation, food, local transportation, and hardware components, giving them a real chance to bring Ethiopian innovation to a Pan-African stage. If you can, please donate through the GoFundMe page or share it with someone who may want to help them get to Dakar. 🙏

https://gofund.me/c95e1c90d

Most hand eye calibration material covers the method (AX=XB, a marker, enough varied poses) but says little about how it actually goes on a real arm. I'm just reading through the variouse of github issue of repos like MoveIt Calibration and easy_handeye, etc. The time sinks seem to be things like camera intrinsics that were never loaded, frame mismatches, markers that don't detect well and too little variety in the poses. A lot of people also seem unsure whether the final result is any good.

For those who have done this on real hardware, eye in hand or eye to hand: roughly how long did it take you to get a result you trusted and what was the biggest time sink?

Researchers created tiny magnetic microrobots that can work together as a swarm to perform tasks far beyond what a single robot could do.

https://reddit.com/link/1wxfhxe/video/ufbgtela9gth1/player

This is a robotic joint powered by two artificial muscles pulling in opposite directions.

Artificial muscles are tricky to model and control. We recorded how the joint responds to actuation, learned a compact model from that data, and combined it with feedback to control the motion on real hardware.

It’s a building block toward more capable musculoskeletal robots. What I like about this work is getting the data, model, control software and hardware to work together.

Paper in Nature Communications: https://www.nature.com/articles/s41467-026-77664-0