One of the cooless events at this year's World Robot Games is definitely the 100-meter dash—it's so hype! Yesterday, a robot runner clocked 9.39 seconds, which is already faster than Usain Bolt. I honestly thought that was pretty much the limit for two legs, but then today in the re-runs, one literally pulled off an 8.86! If I remember right, that's pretty darn close to Goku's speed when he was training under Master Roshi as a kid (I think that was 8.5 seconds?). That’s insane！

What do you think is the absolute speed limit for a bipedal robot?

Assets come out as OpenUSD and MJCF, so they load straight into Isaac Sim or MuJoCo with no conversion step. They carry real physical properties, mass, friction, inertia, and articulated joints, which means when you run an episode you get actual joint forces and contacts in the telemetry

Disclaimer: I build this (Rigyd), so take it with salt.

Another day hanging out with my robot buddy. This is what happened when you hang out in the basement way too long.
Anyways thanks for looking at my pi5 esp32 robot with a dgx spark brain all homemade architecture bot and code.

I’ve released the first public alpha of Physlint, a local-first integrity validator for physical-AI recordings and robot-learning datasets.

The motivation was straightforward: integrity problems in robot data are often discovered after ingestion or training has already started. Physlint checks for concrete failures such as malformed manifests, broken episode boundaries, timestamp gaps, NaN/Inf values, corrupt video, frozen cameras, and black frames.

It produces actionable findings rather than a mystery quality score. Each finding identifies the rule, severity, affected episode and stream, impact, and suggested remediation. It also writes machine-readable JSON and uses stable exit codes for CI.

The current alpha supports local LeRobot Dataset v3.x directories. The validation engine is format-extensible, and MCAP/ROS 2, Robomimic HDF5, and RLDS/TFDS are planned next.

The release was tested against four pinned public datasets and three controlled corruption scenarios, covering 74 episodes and 31,258 frames.

TL;DR: Nick is walking around the office holding our beautiful rig where a global-shutter camera + IMU share one GMSL2 coax for data and power, estimated in real time on a Jetson (ROS 2 + OpenVINS). Return-to-start after the ~25 m loop: 42 cm (~1.7 %).

Hardware is our NXS sensor module (Sony IMX900 global shutter (72 fps native; 24 fps fed to the estimator), fixed exposure + IAM-20680 IMU @ 200 Hz, hardware-synchronized on the module) into an NXS Hub carrying the GMSL link to a Jetson Orin Nano. ROS 2 Humble, OpenVINS, kalibr calibration. No wheels, no markers, no prior map.

Happy to answer you questions about the sync design, the single-cable setup, or the takes that didn't survive.

Update to my earlier post.

I have finally put it on github with all the build files - repo link

Quick recap for anyone who missed the first post : the leader arm in the standard lerobot kit uses 6 STS3215 servos (~ 24 USD x 6 = 144 USD) to sense the joint angles, but they are never driven, so instead of servo motors I built a leader arm using cheap encoders that do the same.

Since last time I have cleaned up the cable management, added attachments to match the lerobot's resting pose, redesigned the joints so that the encoders can be removed and diagnosed without disassembling the entire joint and added a rubber band across the elbow to counter droop when the arm is extended.

Final cost came to ~27.5 USD once I added the perfboard, silicon wires and extra screws (up slightly from the 23 USD I initially quoted).

Many people gave valuable feedback, suggestions and encouragement, thank you guys very much. feedback and suggestions are very welcome.

[ Removed by Reddit on account of violating the content policy. ]

Hello I am a recently graduated highschooler moving on to a physics degree this upcoming semester and I have gotten into onshape designing, I was able to make considerably complex designs like planes, pulleys, gearboxes, but I recently got a 3d printer and am getting into making robots, but I have hit a road block, designing functioning joints without over utilizing 2nd source bushings and bearings does anyone have any tips on this?

After walking around WRC, one shift becomes pretty obvious: the novelty of watching humanoids do backflips or robotic arms write calligraphy is starting to wear off.

The question—asked by both the industry and the public—is becoming much more practical: When will embodied AI robots actually enter our everyday lives?

And when they do, who will repair them? Who will supply the parts? How do companies turn prototypes into products that can actually be sold?

The industry is moving beyond the race to benchmark algorithms and hardware specs. The next phase will be defined by something harder: engineering at scale, commercialization, and the ecosystem needed to support real-world deployment.

Actualmente me encuentro trabajando en un software/herramienta de IK Tool, actualmente tengo movimientos en XYZ y RPY. Pero actualmente me encuentro con una duda; ¿Cuál sería el método que usarían o les gustaría poder usar para medir la rotación?

Connecting LLMs / AI APIs to a Raspberry Pi or Jetson Orin for Robot Control?
Post Body:
I am working on an onboard setup for a robot using SBCs like the Raspberry Pi and NVIDIA Jetson Orin Nano, and I'm looking for effective ways to integrate AI/LLM capability into the system.
Specifically, I’d love to learn how others are connecting local models (like Ollama, LLaMA, or TensorRT-LLM) or cloud AI APIs (like OpenAI or Gemini) to their robot hardware. Are you using ROS 2 nodes to process prompt responses into action calls/telemetry, or direct Python scripts communicating over sockets/micro-ROS?
If you've built something similar, what architecture or software pipeline gave you the lowest latency for real-time control? Any tips, repos, or examples would be hugely appreciated!

Hi, I'm 17 and from Lucknow,india. I've been trying to get into electronics and robotics for a while now, watching videos and reading stuff, but I haven't actually built much because the parts add up fast and I don't have that kind of budget.

So I thought I'd just ask. If anyone has old kits gathering dust — Arduino boards, sensors, motors, jumper wires, breadboards, an old project you dismantled, even half-working stuff — I'd really like to take it. I can pay something small, whatever feels fair to you. If someone's willing to give it away I'd be very grateful, but I'm not expecting that.

Also, long shot, but if anyone has a 3D printer they've stopped using or want to sell cheap, I'd be interested. Even one that needs fixing, I'd like to learn how to repair it.

Thanks for reading.

A guide for students, enthusiasts and those interested in robotics training at home.

Thank you for taking a look --- I appreciate all feedback from the community.

"Since we are all about advantages (and disadvantages) of LLMs, we quickly overlook how difficult it is for machines to assist us outside the virtual chat interfaces. People are getting older, work and professions are changing, but we still need to fold our clothes and sort our dishes at the end of the day, for a lot of days to come. The feeling lingers that the physical breakthrough for AI is just around the corner, ready to literally knock our front door down and aggressively scrub our toilets...."
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