The surge in embodied intelligence has led to a focus on large models, seen as the 'brain' of robots, expected to understand and plan tasks. However, many projects shortcut by combining purchased chassis with self-developed models, resulting in impressive demos that struggle in real-world scenarios. This highlights a critical gap: the disconnect between cognitive understanding and physical execution, as robots often fail to translate commands into actions.
The industry has developed a tendency to prioritize the cognitive aspects of robotics while underestimating the importance of the physical components. This 'heavy brain, light body' approach allows for rapid demo completion but creates significant limitations. Real-world environments present challenges that simulations do not, and even minor obstacles can render advanced cognitive systems ineffective.
The disparity between the cognitive and physical capabilities of robots raises questions about the future of embodied intelligence. While large models enhance cognitive limits, motion control and hardware define the operational baseline. The essence of embodied intelligence lies in the integration of cognition, motion control, and physical embodiment, emphasizing that neglecting physical capabilities can lead to a disconnect between thought and action.
Editor's Note
The robotics industry faces a critical challenge in balancing cognitive capabilities with physical execution. As organizations invest heavily in advanced AI models, the importance of robust hardware and motion control systems cannot be overlooked. This imbalance may hinder the practical deployment of robotic systems in real-world environments, highlighting the need for a holistic approach to embodied intelligence.
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