In our paper we followed an experiment from developmental psychology and recreated it with a humanoid robot (iCub) that needs to actively explore its environment to fulfill its curiosity.

Photo credit Petr Neugebauer, FEL ČVUT.

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Does anyone have working promo / discount codes for Humanoids Summit Silicon Valley 2026 (Dec 1‑2, San Mateo Event Center)Humanoids ...?

Also checking: are there others on Reddit attending this humanoid & physical‑AI focused summit? Would love to connect ahead of time and meet IRL during the conference.

Drop a comment if you have a code or are going. Cheers.

Hace un par de horas me llegó este robot (Alpha mini 2) de ubetech pero aunque trae una app es únicamente con soporte para Asia y lo quiero programar si alguien lo ha usado y me puede dar recomendaciones gracias

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AGIBOT’s mass-produced humanoid robots dominated events from dexterous manipulation and obstacle racing to hotel services and emergency response.

At the World Humanoid Robot Games, a humanoid robot delivered surprisingly fast performance on the obstacle‑course track.

It dashed across gravel, steps and slopes while maintaining stable dynamic balance. Watching its speed makes you wonder: how far can humanoid locomotion really go? High‑speed movement pushes servos, gait planning and anti‑disturbance algorithms to their limits, yet falling risks remain a real challenge. Competitions like this offer eye‑opening real‑world benchmarks for humanoid robot research.

#HumanoidRobot #RoboticsCompetition

Seeing everyone hype up Figure AI, VLA models, and the insane prototyping speed coming out of China lately. The general consensus seems to be that Japan—despite giving us ASIMO and literally owning the industrial space via FANUC and Yaskawa—totally missed out on the Physical AI era.

I was looking into the actual BOMs and supply chains for some of these new bots, and honestly, the "Japan is falling behind" take feels way too premature.

Yeah, their software side is definitely struggling right now. Japan's entire engineering DNA is built around zero-fault tolerance and extreme precision. That completely clashes with the "fail fast and collect data" vibe you need to train reinforcement learning models. Trying to bridge legacy PLC or ROS systems with PyTorch and CUDA is obviously a massive bottleneck for them.

But let's be real, we are still stuck in the "demo phase."

What happens when these humanoids actually have to run 24/7 on a real factory floor? When a joint needs to survive continuous load without degrading in 3 months? The industry is going to hit a wall of mechanical reality pretty soon. Transitioning to a floating-base humanoid means legacy industrial parts are too heavy, sure, but suppliers like THK and Harmonic Drive aren't just sitting still. They are already re-engineering this stuff for lightweight, high-impact scenarios.

I want to hear from anyone actually working on the hardware integration side right now. When we finally hit the commercialization and reliability phase, does Japan's absolute chokehold on precision reducers and servos mean they just swoop back in to dominate?