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⚡️EgoVerse is a first-of-its-kind, collaborative ecosystem for human-to-robot learning. The consortium leverages Project Aria to capture high-fidelity, egocentric human data — including 3D hand and head poses — to train next-gen robot manipulation policies. With over 1,300 hours of data across 2,000+ tasks, EgoVerse is a prime example of...

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Project Aria @Meta

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18,153 Aufrufe • vor 6 Monaten •via X (Twitter)

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Understand the dataset in 1 shot below

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egocentric human data is the unlock for robot manipulation. meta's been sitting on this goldmine

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Mecka is excited to power EgoVerse: a growing ecosystem for robot learning from egocentric human data Proven across 4 leading research labs, EgoVerse data consistently boosts robot performance We release the tools for anyone to collect data, inference/train, and contribute! 🧵
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Mecka is excited to power EgoVerse: a growing ecosystem for robot learning from egocentric human data Proven across 4 leading research labs, EgoVerse data consistently boosts robot performance We release the tools for anyone to collect data, inference/train, and contribute! 🧵

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Introducing EgoVerse: an ecosystem for robot learning from egocentric human data. Built and tested by 4 research labs + 3 industry partners, EgoVerse enables both science and scaling 1300+ hrs, 240 scenes, 2000+ tasks, and growing Dataset design, findings, and ecosystem 🧵
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Imitation learning has a data scarcity problem. Introducing EgoDex from Apple, the largest and most diverse dataset of dexterous human manipulation to date — 829 hours of egocentric video + paired 3D hand poses across 194 tasks. Now on arxiv: (1/4)
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Project Aria is a research program helping Meta unlock new possibilities of how we connect with and experience the world through AR and AI. 📺Watch the full tutorial from #CVPR2022 to learn how Project Aria will advance machine perception and AI research:
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Privacy-first research is the core of everything we do at Project Aria. 🛡️✨ We’re thrilled to release EgoBlur Gen 2—our next-gen open-source solution for preserving privacy in egocentric video. Key Features: ✅ Optimized for Gen 2! Tuned for high-res data & next-gen hardware ⚡️ ✅ Native for VRS, MP4, JPEG, and PNG EgoBlur Gen 2 helps you automatically detect and obscure faces and license plates on egocentric cameras from Aria Gen 2 with ease. 🔍 Dive into the models: 👉
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Data is the core bottleneck for robotics, here is the solution: Introducing MicroAGI00: We open sourced 1M+ frames of egocentric human long horizon mobile manipulation data. Scaling to 300M by Dec '25 and 100B frames Q4 2026 dm if you want your robot to wipe your office 🧵

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Introducing Gen-HumanEgo, a more training-ready open-source egocentric human data for robot learning. We are here to turn real-world human experience into training-ready data, designed to help models learn better. Gen-HumanEgo is a start. Open source now on HuggingFace.

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Qwen-VLA feels like one of the first real robotics foundation models. A single system trained across robot manipulation, navigation, egocentric human video, simulation, and vision-language reasoning instead of isolated robot policies.
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Qwen-VLA feels like one of the first real robotics foundation models. A single system trained across robot manipulation, navigation, egocentric human video, simulation, and vision-language reasoning instead of isolated robot policies.

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Helix is now learning directly from human video data We have already trained on data collected in the real world, including Brookfield residential units To our knowledge, this is the first instance of a humanoid robot learning navigation end-to-end using only human video

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VLAI Robotics Launches High-Dexterity Dual-Arm Robot Starting at ~$5,500 USD VLAI Robotics, utilizing the open-source design of Japan’s OpenArm team, has introduced a high-dexterity, low-cost bimanual robotic system. The product is priced from 39,900 RMB (approximately 5,500 USD), making high-level research tools accessible to institutions and developers. The robot features a human-scale, arm-hand integrated design with up to 16 DOF (8 DOF per arm, including the gripper). It can handle a dual-arm peak payload of 12 kg while maintaining high precision. A key breakthrough is its ability to replicate human upper limb movement trajectories, which enhances data quality for imitation learning and remote operation. VLAI Robotics handled the domestic engineering, manufacturing, and VLA (Vision-Language-Action) algorithm integration, with quality control organized according to the strict standards of the OpenArm R&D framework. The robot is highly adaptable for research, education, and Physical AI training, supporting easy expansion for features like VR teleoperation.

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