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The “Brain–Cerebellum” Collaborative Architecture Accelerates the Evolution of Embodied Intelligence
Release time: 2026-06-01
Currently, the deep interdisciplinary integration of artificial intelligence, mechatronics, control science, materials science, and neuroscience is underway, with the co‑evolution of robots’ “cerebellum” and “cerebrum” emerging as a key competitive focus in the fields of embodied intelligence and humanoid robotics. The “brain–cerebellum” architecture has been designated as a priority area for the development of the embodied intelligence industry.
In the technical architecture of a robot, the “body,” the “brain,” and the “cerebellum” are interconnected and mutually complementary in function. The body serves as the robot’s physical foundation, encompassing all the hardware components necessary for executing motions and perceiving the world. The “brain” typically refers to the central computing unit or system, which runs sophisticated AI algorithms—such as deep-learning models for object recognition and scene understanding, natural-language-processing models for voice interaction, reinforcement-learning models for policy optimization, and simultaneous localization and mapping (SLAM) algorithms for autonomous navigation. Meanwhile, the “cerebellum” draws inspiration from the biological cerebellum: rather than engaging in high-level reasoning, it focuses on translating the brain’s high‑level directives into precise, coordinated, and stable low‑level motor control signals, while also providing rapid, real-time compensation and regulation in response to external disturbances and internal errors. Together, these three components form a highly coupled, collaboratively operating organic whole, linked by high-speed data buses and a well-defined control hierarchy.
From the perspective of industrial policy, the Ministry of Industry and Information Technology (MIIT) explicitly stated in its “Guiding Opinions on the Innovative Development of Humanoid Robots” that it will establish a comprehensive technological innovation system for the humanoid robotics industry, encompassing key technology clusters for the robot’s “brain,” “cerebellum,” and limbs. Led by breakthroughs in large‑model and other artificial intelligence technologies, this framework will drive the continuous iterative advancement of robotic technologies. Furthermore, the 2026 Government Work Report called for fostering and developing future industries, including embodied intelligence.
In the field of cerebellar‑inspired robotics, a research team has recently proposed a general‑purpose motion‑control framework aimed at addressing the challenge of balancing motion fidelity and stability in highly dynamic environments. This work demonstrates that a single control strategy can enable a robot to perform a variety of complex dance movements, achieving an overall success rate exceeding 90% across diverse scenarios, thereby laying the groundwork for precise manipulation in industrial settings.
Industry experts note that the current core research priorities in the field of embodied intelligence are concentrated in three major areas: large-scale embodied models, VLA (vision–language–action) models, and world models. As the capabilities of these large models continue to improve, robots will transition from constrained, closed‑environment settings to broader, open‑world scenarios, paving the way for large‑scale real‑world deployment. In industrial settings, structured environments and well‑defined task boundaries provide favorable conditions for the early adoption of embodied intelligence. Over the next few years, the “brain–cerebellum–proprioception” collaborative architecture is expected to evolve further, driving industrial robots toward a full transformation—from rigidly programmed executors to adaptive, intelligent agents.
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