Physical AI Data Infra,from human for human.
Joined September 2025
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Congrats to Nature Will on the launch of Natura-1! 🚀
We’re proud to see our real-world data powering Natura-1, Nature Will’s first general-purpose foundation model.
Honored to be part of this journey.
That’s a wrap on #IROS2026!
What an incredible few days in Pittsburgh.
A huge thank you to everyone who stopped by GenRobot Booth 637 — researchers, builders, industry partners, and robotics enthusiasts from around the world. We loved the conversations, questions, ideas, and connections around Human Data for Embodied AI.
Every conversation gave us new perspectives on what the next generation of Physical AI needs — and motivates us to keep pushing forward.
We’re just getting started. We’ll keep turning real-world human experience into new possibilities for embodied AI.
Thank you, Pittsburgh. See you at the next one! 👋
Congratulations to our partner Simate on developing its proprietary Physical RSI system and taking the top spot on the RoboDojo leaderboard!
🏆 Congrats to our partner Simate! Simate-beta ranks #1 on RoboDojo-Sim’s Long-Horizon benchmark.
Built with our data collection hardware.
Trained entirely on our data.
Proud to help robots take on longer, more complex tasks. 🚀
#Genrobot #Robotics #EmbodiedAI
Get it running now👉genrohub.com/blog/gen-human-…
Introducing Gen-HumanEgo, a more training-ready open-source egocentric human data for robot learning.
Powered by our Data Foundation Model (DFM), synchronized Ego video is transformed into training-ready signals: video, action, robust hand tracking, depth, semantic annotations are precisely aligned and encoded into unified tokens — creating a shared representation.
We are here to turn real-world human experience into training-ready data, designed to help models learn better.
Gen-HumanEgo is a start.
#EgoData #Opensource #EmbodiedAI
3 days to IROS 2026.
GenRobot.AI is getting ready to meet the researchers, builders, and innovators shaping the future of embodied AI in Pittsburgh.
We’re bringing our latest work on Human Data for Embodied AI to Booth 637.
Come explore how diverse, real-world human data can help scale Physical AI beyond the lab.
📍 Booth 637
📅 Sep 28–30
📌 Pittsburgh, PA See you at IROS.
#IROS2026 #EmbodiedAI #HumanData #PhysicalAI #Robotics
Genrobot.AI retweeted
Introducing Gen-HumanEgo, a more training-ready open-source egocentric human data for robot learning.
Powered by our Data Foundation Model (DFM), synchronized Ego video is transformed into training-ready signals: video, action, robust hand tracking, depth, semantic annotations are precisely aligned and encoded into unified tokens — creating a shared representation.
We are here to turn real-world human experience into training-ready data, designed to help models learn better.
Gen-HumanEgo is a start.
#EgoData #Opensource #EmbodiedAI
Introducing Gen-HumanEgo, a more training-ready open-source egocentric human data for robot learning.
Powered by our Data Foundation Model (DFM), synchronized Ego video is transformed into training-ready signals: video, action, robust hand tracking, depth, semantic annotations are precisely aligned and encoded into unified tokens — creating a shared representation.
We are here to turn real-world human experience into training-ready data, designed to help models learn better.
Gen-HumanEgo is a start.
#EgoData #Opensource #EmbodiedAI
Introducing Gen-HumanEgo, a more training-ready open-source egocentric human data for robot learning.
Powered by our Data Foundation Model (DFM), synchronized Ego video is transformed into training-ready signals: video, action, robust hand tracking, depth, semantic annotations are precisely aligned and encoded into unified tokens — creating a shared representation.
Open-source now: huggingface.co/datasets/genr…
Join our Discord community to connect with the team and other builders: discord.gg/rSSb5thgu
Contact Us: [email protected]
Swinging. Turning. Jumping.
@GenrobotAI DFM turns six-camera Ego video into continuous whole-body mesh and skeleton data, preserving body structure and temporal consistency even during fast motion and complex poses.
See the Whole Body. Learn the Whole Skill.
#GenRobot #WholeBodyData #egodata
#PhysicalAI #Robotics
Bending. Squatting. Moving.
DFM reconstructs continuous whole-body meshes from Ego video, even with partial occlusion.
~3 cm mean whole-body error.
See the Whole Body. Learn the Whole Skill.
#GenRobot#WholeBodyData#ego data
#PhysicalAI #Robotics
IROS 2026｜Meet @GenrobotAI in Pittsburgh – Human Data for Embodied Intelligence
We are excited to announce our participation in IROS 2026! We warmly invite researchers, industry leaders, and innovation partners from around the world to join us in Pittsburgh. Together, we'll delve into the frontier of embodied AI, explore breakthroughs in perception-action integration, and discuss pathways to real-world impact across industries.
📅 Date: September 28–30, 2026
📍 Venue: David L. Lawrence Convention Center, Pittsburgh, USA
📌 Booth: 637
We look forward to connecting with you in Pittsburgh — and exploring the future of embodied intelligence through Human Data together!
#Genrobot #humandata #egodata
Genrobot.AI retweeted
Reliable Whole-Body Data is more than a human-looking mesh.
It requires accurate ground truth, temporally consistent motion, and a production pipeline built to scale.
Reliable Whole-Body Data is more than a human-looking mesh.
It requires accurate ground truth, temporally consistent motion, and a production pipeline built to scale.
😄Our internal evaluations show:
<30s on-site calibration
<0.4 px reprojection error
Built on this ground truth, DFM（Data Foundation Model） reconstructs continuous whole-body motion from partial egocentric observations.
~3 cm mean full-body reconstruction error
~2 cm upper body / ~3.5 cm lower body
And the output goes beyond body mesh: whole-body motion, two-hand tracking, objects, contact states, egocentric observations, and action semantics—all aligned in one shared spatiotemporal coordinate system. From ingestion and reconstruction to quality validation, frame filtering, and training-format export, the entire pipeline is automated. Watch the video to see whole-body motion captured during a music practice session.
Read more about our blog post👉：genrobot.ai/blog/whole-body
How do you scale whole-body data?
😜Start with Ego！
Vision-only，whole body mesh！
≈3 cm whole-body error
100K hours/month.
From real-world human behavior to policy-ready Whole-Body Manipulation Data—at scale.
See the Whole Body.
Learn the Whole Skill.
#PhysicalAI #Robotics
Genrobot.AI retweeted
How do you scale whole-body data?
😜Start with Ego！
Vision-only，whole body mesh！
≈3 cm whole-body error
100K hours/month.
From real-world human behavior to policy-ready Whole-Body Manipulation Data—at scale.
See the Whole Body.
Learn the Whole Skill.
#PhysicalAI #Robotics