Embodied intelligence solves pain points in mountain farming, and the project secures seed-round financing.

In the vast rural areas of China, especially in mountainous and hilly regions, a silent crisis is spreading: the labor force is seriously aging, with those over 55 years old accounting for more than 35% of the practitioners. On the steep slopes, the dilemma of "arable land without farmers to cultivate" is becoming increasingly prominent. Meanwhile, in the mountainous and hilly areas, which account for more than one-third of the country's cultivated land, due to fragmented plots and complex terrain, traditional large agricultural machinery is almost useless, leaving a huge gap in the market for small intelligent agricultural machinery. It was by perceiving this sharp contradiction that a young startup team officially launched the "Mountain Adaptive Embodied Intelligence Agricultural Project" in July 2023, aiming to provide a solution to this problem with innovative embodied intelligence technology.

Full-stack self-research of power modules and technological breakthroughs in realizing intelligent agricultural operations in complex geographical environments

The core motivation of the project stems from a profound understanding of the industry's pain points. From concept to realization, the project has gone through a practical and tortuous exploration path. The project team consists of two core members: Wen Haozhe, a serial entrepreneur, has in-depth knowledge of core hardware and top-level logic. He led the research and development of the reducer, completed all-round 3D modeling, and was responsible for the construction of algorithms and AI models. Another partner, Yang Chaowei, focuses on circuit design and electrical systems. With strong professional capabilities, he ensured the robustness of the project's underlying power control and system integration.

Starting from scratch, they focused their technical route on full-stack self-research of "brain-machine-electricity". At present, the project has successfully developed a key low-cost self-developed joint power module, and controlled the proofing cost at around 250 RMB, far lower than the industry average, laying a solid foundation for the low-cost of the whole machine. At the same time, the decision-making architecture based on the visual language model has been established and is steadily iterating along the path of evolving towards the VLA large model. The self-developed high-response joint power components have high universality. By matching different reducers, they can be applied to unmanned vehicle chassis, robotic arms, and drones at the same time, achieving the ultimate cost optimization and supply chain simplification of "same core, different speeds".

Market strategic penetration and the optimization of agricultural labor cost structure by the robot service model

In terms of market prospects, there are broad opportunities. Relevant data shows that the scale of the Chinese agricultural machinery market will be about 400 billion RMB in 2025, of which small agricultural machinery below 40 horsepower accounts for more than 60%. The project precisely targets this blue ocean market. Its solutions can not only be used for the picking, transportation, and plant protection of cash crops such as tea and coffee, but also can be smoothly transferred to complex terrain inspection scenarios such as power line inspection and forest disaster prevention in the future.

In terms of business model, the project shows flexible survival wisdom. Its business logic is "low-threshold entry, high-frequency service, and in-depth profit sharing". At the hardware level, through extreme cost control, the selling price of the whole machine is reduced to less than one-third of that of traditional products. The profit mainly comes from subsequent operation service subscriptions (RaaS), data value-added services, and finally, the premium sharing of agricultural products. This model significantly reduces the initial investment risk of farmers. Taking a 100-acre coffee plantation as an example, after adopting the RaaS service model, farmers can directly save more than 50% of the cost in the first year. At the same time, due to the quality improvement brought about by standardized operations, they can also get a higher purchase price.

The long-term evolution of embodied intelligence technology in the construction of the smart agriculture ecosystem

Regarding future planning, the team has formulated a clear three-step strategy. The short-term goal is to obtain initial cash flow by selling self-developed joint modules; the medium-term goal is to focus on promoting the RaaS service model, deeply penetrate the target market, and continuously accumulate data; the long-term vision is to become a digital asset operator in unstructured environments, provide quality endorsements for agricultural products through the accumulated planting behavior data, and participate in the value distribution of the downstream supply chain.

In the view of the team, the value of this project lies not only in realizing the intelligent, miniaturized, or unmanned operation of agricultural machinery, but also in a fundamental transformation of the thinking paradigm - from "managing existing cultivated land" to "creating new cultivated land". Through embodied intelligence technology, the marginal soil that was previously regarded as "abandoned cultivated land" due to its steepness and fragmentation can be re-integrated into the production factor sequence. This transformation is not only a supplement to the existing labor force, but also a re-development of land resources through digital means, transforming natural barriers into substantial agricultural production capacity.

Looking back on the entrepreneurial journey, the founder deeply feels that challenges and opportunities coexist. The team's greatest experience is that in hard-tech entrepreneurship, a sense of awe for the physical world and extreme practical engineering capabilities are more important than any advanced concepts. They will continue to delve deep into this field, aiming to make intelligent robots truly enter the fields and become a new productive force to support rural revitalization.