On May 29th, the 2025 Zhangjiang Embodied AI Developer Conference and International Humanoid Robot Skills Competition kicked off at the Zhangjiang Science Hall in Pudong, Shanghai. Concurrently, nine developer forums unlock cutting-edge technologies and industry trends online.

Ye Yangsheng, co-founder of SEER Robotics, was invited to attend the Humanoid Robot Ontology Forum and delivered a speech titled “From Technological Imagination to Industrial Reality: The Commercial Landing of Embodied AI.” Ye analyzed the core challenges of humanoid robots transitioning from technological breakthroughs to large-scale commercial adoption, focusing on three major pain points—limited data, weak feedback, and low controllability—while systematically outlining solutions and industry prospects.

Landing Challenges: Data, Feedback, Controllability

In his speech, Ye dissected the core obstacles currently hindering humanoid robots' journey from technological breakthroughs to commercial application: data dilemmas, feedback limitations, and low controllability.

Humanoid robots require massive amounts of data for training, but collecting data in real-world environments is extremely costly. According to calculations by the National Humanoid Robot Innovation Center, training a humanoid robot to sort batteries requires gathering tens of thousands of grasping actions. It involves variables such as lighting, angles, and materials, with a single data collection session costing over a thousand yuan. Additionally, the inherent differences between humanoid robots and natural human behavior result in generated data that deviates from real-world scenarios, making it difficult to effectively support model training.

Human skin has numerous sensory units, but traditional sensors struggle to replicate the real-time responsiveness of human touch, failing to achieve the same level of real-time responsiveness. In contrast, autonomous driving has advanced rapidly due to the similarity between visual perception and human eyes, while humanoid robots still face challenges in achieving comparable sensor data precision.

To achieve human-like form and functionality, humanoid robots require a large number of drives, motors, and joints, with 40+ degrees of freedom. This highly complex multi-joint system significantly increases the complexity of motion control algorithms, making multi-joint coordination vastly more challenging.

Breakthrough Path: Technological Innovation and Ecosystem Synergy

Facing these industry challenges, Ye detailed SEER Robotics' two breakthrough strategies: "New Technology + Old Products" and "Old Technology + New Products."

"New Technology + Old Products" involves validating the feasibility of embodied AI technologies through unmanned forklifts by integrating cutting-edge technologies such as multi-layer semantic mapping, end-to-end navigation, vision-language-action models (VLA), and reinforcement learning into traditional forklifts.

Data Reuse Advantage: 
Directly leverages historical operational data from human drivers, avoiding the data scarcity issue faced by humanoid robots.

Simplified Feedback Mechanism: 
Requires only basic force sensing and visual positioning, eliminating the need for high-cost tactile sensors.

Low-degree-of-freedom Control: 
Focuses core control on wheel steering and forklifting, avoiding the complexities of multi-joint coordination.

"Old Technology + New Products" leverages SEER Robotics' mature control systems to develop a new embodied AI controller for humanoid robot development.

Building on our long-term expertise in intelligent robot control systems, SEER Robotics has launched the world's first integrated embodied AI controller, the SRC-5000. Currently, this controller has entered mass production, and the first embodied AI wheeled humanoid robot based on it can already collaborate with other intelligent robot systems. In the second half of this year, SEER Robotics plans to partner with industry allies to release more embodied AI products powered by the SRC-5000.

In conclusion, Ye stated that SEER Robotics will continue to drive the development of humanoid robots and embodied AI through our dual-flywheel model of "Technology Flywheel + Platform Flywheel." By supporting more companies in developing intelligent robots with our mature control systems, SEER aims to enrich the robotics ecosystem across upstream and downstream sectors, building a complete industrial loop from core components to real-world applications. Simultaneously, leveraging AGI technology to accumulate scenario data will further strengthen the "AGI brain," lowering the entry barrier for the intelligent robotics industry.