Tae Hoon Yang

Member of Technical Staff @RewardAI_

[Weizhuo(Ken) Wang @KenWangWeizhuo]

A person walks around campus for 5 hours with cameras.
That's it. That's the training data.
The result? A humanoid robot that traverses unseen buildings, crowds, and glass walls — zero robot data, zero finetuning.
EgoNav is here.
https://t.co/PjOww2O6N8

None of these behaviors were pre-programmed:
• Waiting for a door to open before entering
• Steering around glass walls invisible to depth sensors
• Yielding to pedestrians and resuming
• Re-routing when furniture is rearranged
All emerged from 5 hours of a human walking around. The prior is real. (1/6)
#Humanoid #Robotics #DiffusionModel #EgoNav

[Haochen Shi @HaochenShi74]

Excited to release Minimalist Compliance Control! We achieve robust, compliant robot interaction across robot arms, dexterous hands, and humanoids, with NO force sensors or learning. If you’re wondering what remains, please see the thread below😉
Website: https://t.co/FdEnntwRXr

[Tae Hoon Yang @taeyang___11]

Everything is open sourced thanks to @HaochenShi74, @jc_hu0822, @ZhicongZha97226, @DanielJian6777, @KenWangWeizhuo, @YaoHE09, @zhenkirito123, @MattChenYM, @YifanHou2 and the constant support from our amazing advisors, @monroe_kennedy3, @ckarenliu, and @SongShuran.

7/7

[Tae Hoon Yang @taeyang___11]

Excited to introduce Locomotion Beyond Feet!! A whole-body locomotion system that enables humanoid robots to crawl, climb, and recover using hands, knees, elbows, and torso, extending locomotion beyond legs alone.

Project Page: https://t.co/catSmExed6

1/7

[Tae Hoon Yang @taeyang___11]

Yes, it falls sometimes. And yes, it gets back up on its own 💪When the robot falls during real-world deployment, IMU signals combined with depth-based perception identify the fall configuration and trigger the appropriate recovery skill policy to autonomously stand back up!

6/7