Core Viewpoint - The article discusses the evolution and significance of embodied intelligence, emphasizing its philosophical roots and the necessity of physical interaction for intelligent systems [4][5][7]. Group 1: Historical Development - The concept of embodied intelligence traces back to philosophical and cognitive science developments, highlighting the importance of physical interaction in cognitive processes [4]. - Key experiments, such as Richard Held's "passive movement cat" study, demonstrate the intrinsic link between perception and action, reinforcing the idea that active engagement with the environment is crucial for learning [5]. - The shift from traditional views of intelligence as disembodied computation to a more integrated approach that includes physical embodiment is outlined [6][7]. Group 2: Current Trends in Embodied Intelligence - The construction of immersive environments for embodied intelligence is essential, requiring the integration of physical properties and sensory feedback [9][10]. - The development of large-scale, systematic robot training facilities is identified as a critical infrastructure for advancing embodied intelligence [12]. - Various high-level robot training platforms are emerging across China, indicating a rapid growth in this sector [12]. Group 3: Data Collection and Training - High-quality, diverse behavioral data is crucial for the development of embodied intelligence, focusing on visual, interaction, and semantic understanding data [15][17]. - The article outlines the importance of structured data collection methods, including teleoperation and wearable devices, to enhance the training of robots [19][20]. - A systematic approach to data collection is emphasized, with a focus on stability in object grasping tasks, leading to improved predictive capabilities in robotic systems [22][23][25]. Group 4: Future Directions and Challenges - The integration of embodied intelligence with large models is seen as a key pathway for advancing robotic technology, emphasizing the need for a collaborative framework between edge and cloud computing [26][29]. - The article discusses the necessity of building a comprehensive training ecosystem that combines real and virtual environments to facilitate effective learning and adaptation [34][35]. - The future of embodied intelligence relies on diverse embodied agents and a robust learning and evolution framework to ensure continuous improvement and adaptability [31][36]. Group 5: Practical Applications - Embodied intelligence is being applied in various sectors, including logistics, consumer electronics, and healthcare, showcasing its potential to address real-world challenges [30][33]. - The establishment of training centers and collaborative platforms is crucial for fostering innovation and standardization in the field of embodied intelligence [42][45]. - The article highlights the importance of open-source ecosystems and collaborative efforts among industry players to drive advancements in embodied intelligence [74].