"YuanCe Future" Secures Hundreds of Millions in Series A Funding, Targeting Embodied Intelligence to Build the OpenAI of Humanoid Robots

General-purpose whole-body embodied intelligence company Archon Robotics (website: www.archon.tech) recently completed its Series A funding round, raising several hundred million RMB. Investors include leading funds such as Gaorong Ventures, ZhenFund, IDG Capital, and 5Y Capital, as well as Gobi Partners' joint fund with The University of Hong Kong, MiraclePlus, and Shanghai Academy of AI for Science. The capital will primarily fund R&D on a whole-body humanoid foundation model, multimodal whole-body motion data collection, talent acquisition, and the establishment of multi-city R&D centers and industrial partnerships — accelerating the open-source release of its humanoid base model within this year.

Founded in April 2026, Archon Robotics focuses on developing a general-purpose whole-body humanoid foundation model, building what it calls Whole-body Intelligence to give humanoid robots human-like capabilities in whole-body locomotion and manipulation, bringing embodied intelligence into every household.

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Archon Robotics founder Dr. Hongyang Li is currently an assistant professor at The University of Hong Kong, assistant dean at the School of Computing and Data Science, and a mentor at Shanghai Academy of AI for Science. His end-to-end autonomous driving project UniAD won Best Paper at CVPR 2023 — the only work from a mainland Chinese institution to receive this honor in the past decade. In 2026, he received the RSS Early Career Award, becoming the first Chinese scholar in the award's 20-year history.

Co-founder and CEO Dr. Tianyu Li, among the first graduates of Shanghai Academy of AI for Science and a PhD from Fudan University, was a core developer of Huawei's mass-production autonomous driving system ADS 4.0's world engine solution. A distinguished young scholar in end-to-end autonomous driving and embodied intelligence, he was selected for Alibaba Cloud's ModelScope EAI Academic Rising Stars 20 in 2025.

Co-founder and Head of AI Dr. Li Chen graduated from Shanghai Jiao Tong University's Zhiyuan Honors Program and received the HKU Presidential PhD Scholarship. As first author of the UniAD best paper, he is an outstanding young researcher in embodied intelligence and world models, winner of the 2024 WAIC Yunfan Award Rising Star, and was invited to serve as area chair for ECCV 2026.

Archon Robotics' core team comes from top institutions including The University of Hong Kong, Tsinghua University, Shanghai Jiao Tong University, Fudan University, and Zhejiang University, with deep experience in leading autonomous driving, robotics, and large model research groups. High-level autonomous driving and humanoid robotics share highly similar underlying logic. Archon's combination of breakthrough capabilities in frontier original algorithms and massive-scale industrial system deployment allows the team to translate mature complex systems engineering directly into rapid evolution of robotic brains.

The Archon team toasts at Everest Base Camp

Building a General-Purpose Whole-Body Humanoid Foundation Model
Based on Human Body Learning

The embodied intelligence industry is now entering a critical moment of divergence. Yet most current approaches carry inherent limitations: existing training data consists mainly of desktop first-person video, single-arm or gripper movements, missing the native human interaction logic of whole-body center-of-mass adjustment, torso leverage, and multi-limb coordination. This means most robots can only perform fixed-point grasping, struggling to autonomously adapt to variable daily tasks like pushing doors, making beds, or opening doors while holding objects with both hands — all requiring whole-body coordination.

As Archon Robotics CEO Tianyu Li puts it: "The embodied datasets available on the market appear vast, but the information truly effective for whole-body humanoid training is extremely limited."

First-person video datasets only capture what the human eye sees, missing critical pose information beyond hand appearance — squatting, bending, turning sideways. Annotated data for robotic arms and grippers mostly stays in planar scope, recording only end-effector trajectories. Models can learn how the manipulator moves but not how to interact with the environment. Meanwhile, real humanoid robot data is already scarce, with collection costs running from hundreds to nearly a thousand RMB per hour, leaving composite task samples involving whole-body multi-joint coupling almost blank in past data pools.

Each of the three data types has its gaps, all pointing to the same problem — the core information of how humans complete daily actions, namely how the whole body coordinates, how center of mass shifts, how force transmits from lower to upper body, is barely recorded in existing data.

"The long-term absence of this information locks current robotic capabilities at the level of fixed desktop grasping, with a data chasm separating them from the diverse tasks of real home environments," Li says. "To break through this ceiling, we must go back to the source and redefine the logic of data collection."

Therefore, Archon Robotics has chosen to target a nearly unexplored domain: building a general-purpose whole-body humanoid foundation model, with a core concept called Human Body Learning — learning human whole-body poses and coordination patterns rather than merely tracking end-effector trajectories. By studying whole-body human movements, robots acquire the "wisdom of limb coordination" and complete whole-body interaction capabilities.

By embedding humanoid robot action "intelligence" as much as possible at the midbrain level independent of any specific body, the midbrain learns capabilities not tied to any particular robot. It outputs whole-body motion trajectories rather than joint angle commands for a specific model, giving the model cross-platform transfer potential. As data collection becomes more comprehensive and covers more scenarios, the midbrain's representational power grows stronger, and the range of body types to which Archon's embodied whole-body brain can transfer expands.

Based on this judgment, Archon will build an entirely new data collection system. Founder Hongyang Li believes the evolution path of embodied data is progressing from real-robot teleoperation toward handheld devices and first-person perspectives, with the ultimate destination being human-centric whole-humanoid data containing complete human perceptual elements with whole-body action labels.

Archon Robotics will also introduce multi-dimensional perceptual modalities such as tactile sensing, paired with higher-precision whole-body and hand capture equipment. Tianyu Li believes data diversity and quality matter more than pure scale. "One piece of whole-body data covering center-of-mass movement and torso angle changes carries far higher information density than a hundred pieces of desktop data with only hand trajectories."

How data is collected determines what the model can learn; the model's capability gaps in turn define the next collection targets. Once this "collect-train-feedback" loop is operational, it forms a continuously self-reinforcing data moat: each round of collection and training improves model capabilities, sharpens the system's understanding of "which data is truly useful," and raises the efficiency and quality of the next round.

This tests not only algorithmic engineering capability but also systematic understanding of the fundamental question: what exactly does the model need to learn from the physical world? This understanding is precisely Archon Robotics' core judgment.

Taking the Hard but Right Path
Toward Ultimate Intelligence in the Physical World

Going forward, Archon Robotics plans to release its first humanoid-native foundation model in late 2026. For humanoid robots to truly move from laboratories into homes, what's needed is not a single perfect point demonstration but the ability to work continuously and reliably in complex, dynamic, unstructured home environments. The ceiling of this capability fundamentally depends on how deeply the model understands the physical world.

Archon Robotics chooses to return to the starting point of embodied intelligence to answer this question anew: what kind of body to use, and what kind of data to learn from, determines how far robots can ultimately go. Just as there are no helicopters to the summit of Everest, there is no painless shortcut to general embodied intelligence. Archon is charging toward ultimate intelligence in the physical world with primal reverence for the physical world and wild technical ambition — a charge with no retreat.

Wang Xin, partner at Gaorong Ventures, said: "We deeply admire the Archon Robotics team led by Professor Hongyang Li. They have pure technical ideals, profound insights, and the courage to lead through innovation — never followers. From autonomous driving's UniAD, BEVFormer, and WorldEngine to embodied intelligence's Agibot, WholeBodyVLA, and EgoHumanoid, they continuously prove their ability to innovate consistently and produce world-impact results. Today, Archon has once again chosen the hard but right path, tackling the challenge of a whole-body dexterous manipulation brain for humanoid robots. We are thrilled to participate in Archon's mission and look forward to them becoming a world-class embodied intelligence company."