股 票 研 究 Figure 03 机器人点评 | | | Figure 03 展示家庭应用场景，为规模化生产做准备 [Table_Industry] 机器人 | [姓名table_Authors] | 电话 | 邮箱 | 登记编号 | | --- | --- | --- | --- | | 肖群稀(分析师) | 0755-23976830 | xiaoqunxi@gtht.com | S0880522120001 | | 刘麒硕(分析师) | 0755-23976666 | liuqishuo@gtht.com | S0880525080005 | 本报告导读： 究 报 告 请务必阅读正文之后的免责条款部分 行 Figure AI 推出新一代 Figure 03，依托于 Helix 系统，侧重家庭场景落地，并为规 模化生产做了设计准备，看好其后续场景落地与量产进度。 投资要点： [Table_Report] 相关报告 机器人《谷歌推出最新机器人大脑模型，1X 拟融 资 10 亿美元》2025.09.28 机器人《特斯拉计划召开人形机器人等产品量产 会议》2025.09.21 机器人《Optimus V3 量 ...

Core Viewpoint - The acquisition of 2.1 billion yuan by Zhiyuan Robotics of Shuangwei New Materials marks the first listing of a "embodied intelligence concept" company in the A-share market, indicating a significant shift in the capital landscape of the industry before large-scale commercial deployment has occurred [1]. Group 1: Evolution of Embodied Intelligence Players - The industry is witnessing a divergence in paths among embodied intelligence companies, with many opting for a "self-developed ontology + customized model" approach [2]. - Companies are exploring various system architectures, including end-to-end large model systems and dual-system architectures, to enhance the complexity and generalization capabilities of intelligent agents [4]. - The end-to-end large model approach aims to unify visual, language, and action modules into a single system, reducing processing complexity and emphasizing cross-task transferability and deployment efficiency [5]. - Companies like Xingdong Jiyuan, with its ERA-42 model, exemplify the end-to-end approach by integrating visual, language understanding, and action control [5]. - The dual-system architecture decouples task understanding from action execution, utilizing a large-scale Visual Language Model (VLM) for semantic modeling and strategy planning, while a lightweight Visual Language Action (VLA) module handles execution [6]. - Companies such as Figure AI and Zhongke Xingtu adopt this dual-system approach to enhance system robustness in complex task scenarios [6]. - Some companies, like Yundongchu, focus on hardware innovations, such as hybrid wheeled and legged systems, to improve adaptability to complex terrains [7]. - The differentiation in these technical paths influences data collection and training strategies, as well as the collaboration between ontology and intelligent agents, affecting market deployment and business model development [8]. Group 2: Leading Companies in Mainstream Technology Paradigms - The technical routes taken by companies reflect their strategic expressions, with variations in data systems and ontology solutions being significant factors in their market positioning [9].