Core Insights - The article emphasizes the significance of "Embodied Intelligence" in the pursuit of General Artificial Intelligence (AGI), highlighting the need for intelligent agents to perceive, reason, and act in the physical world [3][5] - The integration of physical simulators and world models is identified as a promising pathway to enhance the capabilities of robots, enabling them to transition from merely "doing" to "thinking" [3][5] Summary by Sections 1. Introduction to Embodied Intelligence - Embodied Intelligence focuses on intelligent agents that can autonomously perceive, predict, and execute actions in complex environments, which is essential for achieving AGI [5] 2. Key Technologies - Two foundational technologies, physical simulators and world models, are crucial for developing robust embodied intelligence. Physical simulators provide safe and efficient environments for training, while world models enable internal representations of the environment for predictive planning and adaptive decision-making [5] 3. Research Contributions - The article reviews recent advancements in learning embodied intelligence through the fusion of physical simulators and world models, analyzing their complementary roles in enhancing agent autonomy, adaptability, and generalization capabilities [5] 4. Robot Capability Classification - A five-level capability classification system for intelligent robots is proposed, ranging from IR-L0 (basic execution) to IR-L4 (fully autonomous), covering dimensions such as autonomy, task handling, environmental adaptability, and social cognition [8][15] 5. Core Technology Review - The article systematically reviews the latest technological advancements in legged locomotion, manipulation control, and human-robot interaction, emphasizing the importance of these capabilities in the development of intelligent robots [8] 6. Physical Simulator Comparison - A comparative analysis of mainstream simulation platforms (Webots, Gazebo, MuJoCo, Isaac Gym/Sim) is provided, focusing on their physics engine accuracy, rendering quality, and sensor component support, along with future optimization directions [13][19] 7. World Model Architecture and Applications - The article discusses representative structures of world models, including predictive networks and generative models, and their applications in embodied intelligence, particularly in autonomous driving and articulated robots [14][20]