Post-90s Zhejiang University Advisor Raises Hundreds of Millions for Flying Robots

Flying embodied intelligence company WeiFen ZhiFei (微分智飞) has announced the completion of a Series A2 funding round totaling hundreds of millions of yuan. The round was led by Puhua Capital, with participation from Honghui Fund and the Yangtze River Delta Digital Culture Fund. Existing shareholders including Wuyuan Capital, Shenzhen Capital Group, Hongtai Fund, Huaying Capital, Huakong Fund, Changshi Capital, and BV Baidu Ventures also added investment.

Founded in July 2024, the company has now completed seven funding rounds with total funding exceeding 500 million yuan. Investors span venture capital, industrial capital, and state-owned capital. The company focuses on flying embodied intelligence, building a base model for flying robots based on extreme flight control and complex environment perception. It has been recognized as a national-level potential unicorn enterprise.

Gao Fei, founder and CEO of WeiFen ZhiFei, was born in 1993 and graduated from Zhejiang University with a bachelor's degree and from the Hong Kong University of Science and Technology with a doctorate. After completing his PhD in 2019, he returned to teach at his alma mater, becoming a doctoral advisor at age 28. He currently serves as a tenured associate professor and doctoral supervisor in the College of Control Science and Engineering at Zhejiang University, and has been recognized as a National Outstanding Youth and an Elsevier top 2% scientist. Gao has over a decade of experience in aerial robotics, publishing more than 80 papers and proposing the world's first autonomous flight swarm system for unstructured environments. In 2022, his team's micro flying robot swarm was featured on the cover of Science Robotics. In April 2025, the team published another paper in the journal, achieving acrobatic flight of aerial robots in complex environments.

The core team also includes COO Liu Zhiyang, who holds a PhD and postdoctoral degree from Zhejiang University with more than 30 authorized invention patents, and General Manager and R&D Director Wang Yingjian, a doctoral student at Zhejiang University's FAST Lab with publications at ICRA and IROS. R&D team members hold master's or doctoral degrees at an 80% ratio, hailing from institutions such as Zhejiang University, the Chinese Academy of Sciences, and Hong Kong University of Science and Technology.

Traditional drones rely on human operation or preset routes. WeiFen ZhiFei aims to equip flying vehicles with 'brains.' Gao Fei summarizes the core capabilities of flying robots as a 'three-brain' architecture: the 'cerebrum' handles environment understanding and task decision-making, the 'cerebellum' ensures precise flight control, and the 'swarm brain' manages multi-robot coordination. Technically, the company has developed a 32-gram ultra-lightweight micro flying robot that relies on an on-board low-computing motherboard and limited sensor signals, using a self-developed end-to-end agile control neural network to achieve millisecond-level obstacle avoidance and continuous traversal of ultra-narrow gaps. It also has developed rigid-flexible dual-configuration robotic arms: the flexible arm can extend and retract significantly and grasp compliantly, while the rigid arm is designed for outdoor scenarios, enabling precise grasping and stable transport during flight.

On the product front, WeiFen ZhiFei has launched the intelligent exploration flying robot P300, the industry application flying robot P300 Pro, and the educational and research flying robot FeiTu-alpha. Notably, the P300 does not rely on GPS or manual control and can operate autonomously in complex environments such as mines and underground rail systems. In mining scenarios, the device has undergone over 10,000 real flights in 60-meter-high underground cavities, with modeling error controlled within 1 centimeter. Its products have been deployed in signal-denied environments such as emergency response, mining, and power sectors, forming complete operational capabilities including autonomous mapping, safety assessment, and routine patrols. The products have entered batch delivery, with orders in the hundreds.

Ground embodied intelligence is already a red ocean. According to Qichacha data, as of August 2026, there are 3,572 domestic embodied intelligence-related enterprises, but only a handful focus on 'flying embodied intelligence.' Flying robots face significant challenges to 'fly well.' Gao Fei has noted that data collection is difficult due to high costs and uncontrollable risks, and the complexity of scenarios makes it hard to extract universal rules from significantly different environments. The operation space for flying robots is less controllable than ground, with additional constraints from airflow, obstacles, airspace, and battery life. Between hundreds of orders and large-scale commercial use lie regulatory and technical cost hurdles.

Lead investor Puhua Capital believes WeiFen ZhiFei's value lies in its products' ability to autonomously fly end-to-end in unknown, network-disconnected, GPS-denied, and dark environments, achieving the leap from single-entity intelligence to swarm intelligence. CCTV Fund positions the company as a model for applying physical AI across industries. WeiFen ZhiFei's strategy is to first thoroughly penetrate high-demand scenarios like mining and emergency response, then expand to power, security, and urban services, ultimately aiming to 'connect all industries and fly into every household.'

According to reports, the Series A2 funds will be used for product development, team expansion, and scenario exploration. On the product front, the company will continue to deepen its base models for single-entity and swarm flight intelligence, accelerating product iteration for mining, emergency response, and power scenarios. For the team, it will bring in top technical talent to strengthen its R&D moat. On the market side, it will expand from advantageous scenarios like emergency search and rescue and mining surveying to broader industries such as power inspection and intelligent security.