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].