Core Viewpoint - Embodied AI is becoming a key force in advancing robotics from "executable" to "efficient excellence," addressing current research bottlenecks in hardware adaptability, high algorithm reproduction costs, and the disconnection in the "perception-decision-execution" chain [1][4][21]. Group 1: Research Bottlenecks - Current research teams face three main bottlenecks: insufficient hardware platform adaptability, high costs of algorithm reproduction, and the disconnection in the "perception-decision-execution" chain [1]. - The lack of general-purpose robots to meet the refined needs of multi-modal data collection is a significant challenge [1]. - The complexity of heterogeneous data processing and model training cycles adds pressure to research efforts [1]. Group 2: Technical Sharing Event - A recent technical sharing live stream titled "Frontier Practice of Embodied Intelligence" hosted by Shihe Robotics attracted over 7,000 viewers, focusing on the integration of advanced algorithms with robotic hardware [1][4]. - Dr. Hu systematically analyzed six categories of VLA (Vision-Language-Action) algorithms and demonstrated the reproduction of the RDT (Robotics Diffusion Transformer) model on real hardware [1][4]. Group 3: EA200 Robot Introduction - The EA200 robot, based on Shihe's years of expertise in mobile chassis and dual-arm collaboration, serves as a stable and comprehensive platform for embodied research [7]. - EA200 features a multi-dimensional perception input matrix, enhancing environmental understanding and human-robot interaction capabilities [9]. - The robot's 6-degree-of-freedom arm system supports high-load capabilities and complex dual-arm collaborative tasks, providing quality action execution and sample collection for models like RDT [9][15]. Group 4: Software and Computational Support - EA200 integrates the ROS2 navigation system and proprietary algorithms, supporting a full process from environment mapping to autonomous navigation, significantly reducing the complexity and cost of secondary development [11]. - The robot is equipped with external inference industrial computers and training servers to meet real-time response and large-scale training computational requirements [13]. - EA200 enables multi-modal data collection, model training optimization, and embedded inference deployment, effectively shortening the cycle from algorithm design to experimental validation [13][15]. Group 5: Market Positioning and Value Proposition - EA200 targets the robotics research and education market, providing a complete and user-friendly research support platform for universities, research institutes, and corporate R&D departments [16]. - The robot accelerates research rather than replacing it, standardizing key parameters to lower the threshold for algorithm reproduction and enhance model generalization [16]. - EA200 can simulate various real environments, supporting algorithm validation under different conditions, thus addressing the urgent need for standardized research platforms in embodied intelligence technology [16][18]. Group 6: Future Outlook - Embodied intelligence is positioned as a crucial direction for the evolution of AI and robotics, with VLA algorithms enabling robots to better understand human intentions and execute complex operations [19]. - Shihe Robotics aims to be an "enabler" in this breakthrough, allowing researchers to focus on algorithm innovation while minimizing hardware platform adaptation efforts [21]. - The launch of EA200 marks a significant transition for Shihe from a component supplier to a provider of integrated solutions, reflecting a deep understanding of market pain points and a strategic response to the growing demand for embodied intelligence [21].

文｜富充 编辑｜苏建勋 2025年世界人工智能大会（WAIC）期间最"耀眼"的具身智能论坛，莫过于上海期智研究院举办的"人工智能交叉科学论坛"的主题活动。 这场论坛难得聚齐了当下国内具身智能领域的"伯克利四子"——吴翼、高阳、许华哲和陈建宇，这四位学者均毕业自加州大学伯克利分校，目前都从事具 身机器人相关工作。 其中陈建宇创立了星动纪元，高阳为千寻智能联合创始人、许华哲为星海图联合创始人。吴翼则任蚂蚁集团强化学习实验室首席科学家。 （点击"星动纪元"、"千寻智能"，可查看我们之前的报道。） 这四位的罕见同台，分享内容自然离不开具身智能领域几大核心问题： 具身智能的瓶颈——"获取数据"，这个难题怎么解？ 从简单任务（拿、放），到复杂任务（收拾屋子），机器人从大脑到本体该如何提升？ 已经形成共识的"VLA算法"，里面又有哪些非共识的方法论？ 除了创业者/大厂科学家的身份以外，吴翼、高阳、许华哲和陈建宇四位均担任上海期智研究院PI（Principal Investigator，首席研究员）。 姚期智为图灵奖得主、清华大学交叉信息研究院院长。2005年，姚期智创立"清华学堂计算机科学实验班"（姚班），以培养世界顶尖的 ...

Core Viewpoint - The concept of "embodied intelligence" has been officially included in the 2025 government work report, highlighting its significance in current research by enterprises and educational institutions [1]. Group 1: Challenges in Implementation - Researchers and engineers face challenges when deploying algorithms from simulation environments to hardware, primarily due to insufficient engineering practice and a lack of thorough understanding of classic methods and imitation learning [2]. - These challenges hinder the effective integration of various methods, resulting in suboptimal deployment and performance of VLA algorithms on robotic arms, which obstructs the application of embodied intelligence in real-world scenarios [2]. Group 2: Training Program - Deep Blue Academy has partnered with notable figures and companies to launch an offline training camp focused on robotic arm operation and grasping, aimed at bridging the gap between simulation and real-world application [3]. - The training camp offers hands-on experience with real robotic arms and covers key technologies such as motion planning, visual feedback, imitation learning, and VLA, ensuring a comprehensive understanding of the "perception - decision - control" process [5]. Group 3: Course Highlights - The program emphasizes a full-stack technology loop, providing training from algorithms to hardware engineering capabilities [16]. - It features immersive project practice supported by the hardware platform of Songling Robotics, promoting deep integration of academia and industry resources [16]. - The course adopts a high-density small class format, ensuring intensive technical training and personalized guidance over three days [16]. Group 4: Target Audience - The training is designed for undergraduate and graduate students in robotics and automation-related fields, as well as R&D engineers in the field of robotic arms and embodied intelligence [18].