3个月，完成具身的大脑算法+小脑算法学习！

Core Insights - The article discusses the evolution and current trends in the field of embodied intelligence, focusing on the development of brain and cerebellum modules in robots, which are essential for perception, understanding, and action [3][10]. Technical Evolution - The development of embodied intelligence has progressed through several stages, starting from grasp pose detection to behavior cloning, and now to diffusion policy and VLA models [7][10]. - The first stage focused on static object grasping using point clouds or images, but lacked context modeling for complex tasks [7]. - The second stage introduced behavior cloning, allowing robots to learn from expert demonstrations, but faced challenges in generalization and performance in multi-target scenarios [7]. - The third stage, emerging in 2023, introduced diffusion policy methods that enhance stability and generalization by modeling action sequences [8]. - The fourth stage, anticipated in 2024, emphasizes the integration of VLA models with reinforcement learning and world models, enhancing robots' predictive capabilities and multi-modal perception [9][10]. Current Trends and Applications - The integration of VLA with reinforcement learning improves robots' trial-and-error capabilities and self-improvement in long-term tasks [10]. - The combination of VLA with world models allows robots to predict environmental dynamics, enhancing planning and decision-making [10]. - The addition of tactile sensing to VLA expands the boundaries of embodied perception, enabling more precise and safer operations in complex environments [10]. Educational and Community Aspects - The article highlights the growing demand for engineering and system capabilities in the field, transitioning from theoretical research to practical deployment [14]. - A structured curriculum is proposed to cover various aspects of embodied intelligence, including simulation platforms and model training [14][11]. - The community aspect is emphasized, with active discussions and support for learners in the field [15].