Core Viewpoint - The integration of artificial intelligence and robotics is entering a critical phase, with embodied intelligent robots moving from laboratory settings to industrial applications, driven by advancements in "brain" technology, the resolution of contextual challenges, and rigid demands in specific sectors [1] Group 1: Evolution and Breakthrough of Robot "Brain" - The core competitiveness of embodied intelligent robots lies in the maturity of their "brain" systems, which directly influences their perception, decision-making, and execution capabilities in complex environments [2] - Recent advancements have transitioned robot intelligence from single-modal processing to multi-modal integration, creating a complete technological chain from basic models to comprehensive applications [2][4] - The emergence of visual language models (VLM) has significantly enhanced robots' perception capabilities, allowing them to understand and interact with their environments more effectively [4] - The latest visual language action models (VLA) have integrated motion control into intelligent systems, achieving a closed-loop from perception to action, thus improving operational precision and safety in human-robot collaboration [4][5] Group 2: From Technical Bottlenecks to Scene Implementation - The industrialization of general-purpose robots has been hindered by three main bottlenecks: lack of real machine data, slow model inference, and complex motion control [6] - Focusing on vertical fields provides new pathways to overcome these challenges, facilitating the transition of robots from labs to large-scale applications [6] - The establishment of a "data flywheel" mechanism is crucial for accumulating the necessary 3D spatial and physical interaction data, enabling robots to improve performance through iterative deployment [6][9] - Recent advancements have reduced deployment cycles from 18 months to 6 months and cut deployment costs by 50%, with task success rates increasing from 60% to over 90% [9] Group 3: Key Application Scenarios - The report identifies three key sectors for the application of embodied intelligent robots: apparel, healthcare, and logistics, which are experiencing a pivotal shift from technology validation to large-scale implementation [11] - In the apparel industry, automation bottlenecks have historically limited upgrades, but recent technological breakthroughs are expected to increase automation rates in sewing from 5% to 50% within 3-5 years [11][13] - The healthcare sector faces a significant shortage of caregivers, and robots are being developed to assist in patient care, with government policies supporting the trial of intelligent elderly care robots [13][14] - The logistics industry is focusing on automating the last mile of operations, with embodied intelligent robots addressing the labor-intensive task of picking and sorting, which still relies heavily on human labor [14][16] Group 4: Future Industry Ecosystem and Investment Opportunities - Investment opportunities are emerging in the intelligent robotics sector, particularly in the integration of small and precise models for specific applications, as well as in the development of intelligent sewing equipment in the apparel industry [16][17] - The healthcare robotics field is characterized by multiple technological pathways, with companies exploring various applications in rehabilitation and elderly care [17] - In logistics, the focus is on automated system integration, with companies developing comprehensive solutions that enhance efficiency in material handling and sorting processes [19] - The long-term significance of embodied intelligent robots lies in their potential to redefine production and service paradigms, leading to a new phase of productivity growth in manufacturing and service industries [19]

证券研究报告·行业动态 Figure、1X 新品发布，模型迭代加速人形机器人 商业化落地——2025 年机器人行业系列报告之二 核心观点 本周机器人行业新品连发，①Figure 发布搭载了 Helix VLA 模型 的新品，该模型可以从 VLMs 中提取常识性知识，并将其转化为 可泛化的机器人控制指令，使得人形机器人的学习效率大为提 升，在多个领域实现了第一。②1X 发布 NEO GAMMA，在人工 智能、设计、硬件等方面进行了全面升级，灵巧手采取腱绳结构， 外皮肤覆盖尼龙材料，更适合家庭使用。我们认为模型迭代、供 应链降本，正加速人形机器人商业化落地，预计板块行情继续。 行业动态信息 Figure：发布 VLA 模型 Helix，泛化能力加速机器人通用化发展 2 月 20 日，Figure 推出其自研 VLA 模型 Helix。视频展示了两 个人形机器人在接受人类语言指令后协同工作，拾取并整理此前 未接触过的物件的场景。Helix 模型实现了对于人形机器人的全 上半身控制、多机器人协作、抓取任何物品、单一神经网络、商 业化落地就绪等多项行业第一。其首创的"系统 1、系统 2"架构 的 VLA 模型，在速度和 ...