The latest forecast from IDC shows that the global robot market size is expected to exceed 400 billion US dollars by 2029, with the Chinese market accounting for nearly half of the share. The compound annual growth rate during this period is nearly 15%. In fact, by 2025, driven by policy support and leading enterprises, robots have made progress in multi-modal perception fusion and lightweight model deployment, but some technical challenges still restrict the product performance and cost optimization of embodied robots.
Since the beginning of this year, the embodied robot industry has shown an accelerating development trend. At the end of January, the robot dance performance "YANG BOT" at the CCTV Spring Festival Gala attracted global attention, bringing the robot supplier Unitree Robotics into the spotlight. In March, during the Two Sessions, "embodied intelligence" was included in the government work report for the first time, marking that this field has officially become part of the national strategic planning. In April, the world's first "Humanoid Robot Half Marathon" was held in Yizhuang, Beijing. This was not only a technical demonstration but also represented that embodied intelligence technology has entered a new stage of scenario verification.
"AI + Robotics": A Strategic Engine for Global Development
Currently, "AI + Robotics" technology is accelerating the reshaping of the global industrial landscape and has become a key force driving social and economic development. Embodied robots, as a typical model and strategic direction of the integration of "AI + Robotics", endow physical entities with cognitive decision-making capabilities, breaking through the functional boundaries of traditional robots.
Embodied robots refer to robots that interact with the environment in real time through physical entities to achieve a closed loop of perception, cognition, decision-making and action. Their technical system covers multiple fields such as machine vision, natural language understanding and robotics, and they can achieve deep interaction with the environment through physical entities to realize autonomous learning and evolution. Their application scenarios cover multiple fields such as industry, services and healthcare.
