当老师给我指了VLA作为研究方向后......

Group 1 - VLA (Vision-Language-Action) model represents a new paradigm in embodied intelligence, enabling robots to generate executable actions from language instructions and visual signals, thus enhancing their understanding and adaptability in complex environments [1][3] - The VLA model breaks the limitations of traditional single-task training, allowing robots to make autonomous decisions in diverse scenarios, which is applicable in manufacturing, logistics, and home services [3][5] - The VLA model has become a research hotspot, driving the development of several cutting-edge projects such as pi0, RT-2, OpenVLA, QUAR-VLA, and HumanVLA, fostering collaboration between academia and industry [3][5] Group 2 - The embodied intelligence sector is experiencing rapid growth, with teams like Unitree, Zhiyuan, Xinghaitu, and Yinhai General transitioning from laboratories to commercialization, while tech giants like Huawei, JD.com, and Tencent are actively investing in this field [5] - The course on VLA research aims to equip students with comprehensive skills in academic research, including theoretical foundations, experimental design, and paper writing, focusing on independent research capabilities [13][15] - The curriculum emphasizes identifying research opportunities and innovative points, guiding students to develop their research ideas and complete preliminary experiments [14][15] Group 3 - The course covers the technical evolution of the VLA paradigm, from early grasp pose detection to recent advancements like Diffusion Policy and multimodal foundational models, focusing on end-to-end mapping from visual input and language instructions to robotic actions [8][9] - Core challenges in embodied intelligence, such as cross-domain generalization and long-term planning, are analyzed, along with strategies to combine large language model reasoning with robotic control systems [9] - The course aims to help students master the latest research methods and technical frameworks in embodied intelligence, addressing limitations and advancing towards true general robotic intelligence [9][15]