At the 2026 China International Fair for Trade in Services, the special forum "Physical AI and Embodied Intelligent Robot Innovation Ecosystem Exchange" was held at Shougang Park in Beijing. During the event, Zhang Hengdi, co-founder and CTO of Paisini, delivered a keynote speech titled "Paving the Sensory Foundation for Embodied Intelligence," outlining the company's technological roadmap and industrial vision.

Zhang emphasized that as embodied intelligence ventures into complex, precision-driven tasks, contact-state perception and closed-loop control have become critical bottlenecks. Supplementing physical sensing capabilities such as touch and force perception is essential to overcoming the "Moravec's paradox" and enabling robots to operate effectively in real-world scenarios. During the 14th Five-Year Plan period, Paisini tackled the key "choke point" of tactile sensing in the embodied intelligence field by conquering core materials and sensor structural design, achieving domestic autonomous control over array-based multi-dimensional tactile sensors. Additionally, the company innovatively integrated algorithms with hardware at a deep level, using advanced algorithms to empower hardware technologies, significantly lowering overall application costs and deployment barriers.

In 2026, Paisini launched the world's first self-developed native 6D tactile sensing chip, the GEN4 FUSE. Leveraging this core chip, the company released a new generation of multi-dimensional tactile sensor products, constructing a full-body tactile perception network for robots covering fingers, palms, torsos, and even soles. On the data front, Paisini adheres to a principle of balancing high quality with high richness. On one hand, the company utilizes self-developed data collection gloves and multi-view vision to achieve precise temporal synchronization, accurately recording high-quality physical causal data where "force is the cause, and world state transitions are the effect." On the other hand, it continuously promotes the efficient accumulation of massive data, providing a solid and expansive data foundation for embodied models to deeply learn the relationship between contact states and action outcomes.

Currently, these technologies have been applied to industrial scenarios such as flexible assembly and daily chemical production lines, allowing robots to adjust actions and force output based on contact feedback, driving embodied intelligence from demo validation into highly reliable industrial closed loops. Looking ahead, Paisini plans to further integrate physical signals into model training and robot control, collaborating with industry partners to refine embodied data standards and foster a more vibrant innovation ecosystem.