▲ 12月25日，北京市人民政府新闻办公室举行2026北京亦庄人形机器人半程马拉松新闻发布会。北 京市经济和信息化局、北京经开区管委会相关负责同志出席发布会介绍情况并回答记者提问。北京市 委宣传部对外新闻处处长叶昶主持。 一是加快关键核心技术攻关。 支持高校、科研院所开展前沿技术探索，加强前沿基础 理论创新，针对不同路线做好技术储备；本体方面，组织整机和零部件企业联合定义产 品并开展协同攻关，提升本体硬件水平。系统化推进人形机器人专用芯片自主可控攻 关；具身智能方面，支持企业多模型路线开展工程化实践，推进解决多场景、多任务的 泛化执行问题。 二是提升整机供给、服务和管理能力。 布局国内领先的平台型整机、支持二次开发的 公版机及特色场景专用整机，建设机器人二次开发社区，探索"人形机器人即服务"商业 模式，推动具身智能技术赋能其他机器人产品。以融资租赁推动整机应用，强化机器人 4S店功能，形成可复制的销售、租赁、定制、维修等运营服务模式。率先探索建立产业 相关标准、质量管理与检验检测体系，以及"一机一码"全生命周期管理体系。 三是促进规模化应用落地。 拓展福田康明斯、小米汽车等工业领域场景，打造标杆产 线和工厂。 ...

(年终特稿)从赛场到市场，中国机器人"破茧进化" 中新社北京12月28日电 题：从赛场到市场，中国机器人"破茧进化" 中新社记者 陈杭 这一年，中国机器人以系列突破性进展"闯入"更多应用场景。 从奔跑于全球首个人形机器人半马赛场，到生产线上搬运料箱、安装零件，医院里分拣药品、做手术， 家庭里泡咖啡、叠衣服，课堂上"开讲"，舞台与真人演员一起跳舞……机器人由"技术验证"跨越至"社 会实践"。 2025年，"具身智能"首次被写入《政府工作报告》，党的二十届四中全会审议通过的"十五五"规划建议 将其列为前瞻布局的未来产业之一。中国各地加快布局，北京拟推动万台具身机器人规模落地，培育千 亿级产业集群；上海以物流装配、工业制造、商业零售等领域为牵引，开展场景征集与任务揭榜；深圳 加快具身智能等核心突破，丰富发展人工智能终端新产品，推动产业加快向高向新向优升级。 2025世界人形机器人运动会上"百米飞人决战"夺冠，全尺寸工业人形机器人开启量产交付，机器人应用 于无人药房、无人零售等场景……2025年，中国机器人从赛场奔赴市场，不仅"动起来"更"用起来"。 8月17日，2025世界人形机器人运动会100米决赛在北京国家速滑 ...

中新社北京12月28日电 题：从赛场到市场，中国机器人"破茧进化" 中新社记者 陈杭 2025世界人形机器人运动会上"百米飞人决战"夺冠，全尺寸工业人形机器人开启量产交付，机器人应用 于无人药房、无人零售等场景……2025年，中国机器人从赛场奔赴市场，不仅"动起来"更"用起来"。 8月17日，2025世界人形机器人运动会100米决赛在北京国家速滑馆(冰丝带)举行，以AI自主操控的天工 机器人(右二)以21秒50的成绩获本次比赛冠军。 中新社记者 张祥毅 摄 这一年，中国机器人乘势而起，跑出量产"加速度"。 通过规模化生产与技术迭代，头部厂商推动机器人成本下探与产能升级：加速进化产品全球累计出货量 近1000台，优必选预计到2026年工业人形机器人年产能达5000台，2027年扩大至10000台。 量产表现亮眼，离不开产业链厚积薄发。目前，中国机器人企业已形成覆盖上游关键零部件、中游整机 制造、下游集成应用的完整产业链布局。来自中国机械工业联合会的数据显示，今年前三季度，中国工 业机器人产量达59.5万台，服务机器人产量达1350万套，均已超过2024年全年产量。 北京邮电大学教授方斌在接受中新社记者采访时表示 ...

北京市经济和信息化局副局长姜洪朝在发布会上对近年北京人形机器人产业发展特点进行了介绍。 中新网北京12月25日电 (记者 吕少威)2026北京亦庄人形机器人半程马拉松新闻发布会25日在京举行。 记者从发布会上获悉，北京人形机器人整机单位超过30家，位居国内前列，已培育出北京人形机器人创 新中心、银河通用、松延动力、加速进化、星动纪元等一批国内领先企业。 12月25 产业领域投资并积极引导社会资本投入；另一方面，推动产学研协同创新和国际合作，建设人形机器人 产业育新基地，整合上下游资源形成产业集聚效应，依托机器人半马赛事、机器人运动会、机器人大会 等平台，吸引国际顶尖机构和企业来京交流合作。 姜洪朝表示，2026年是人形机器人进一步加快场景和应用落地的关键一年，也是相关企业加速整机中试 和量产的关键一年。北京市将继续在技术攻关、产品供给、应用落地和产业生态等方面加大支持力度。 加快关键核心技术攻关。支持高校、科研院所开展前沿技术探索，加强前沿基础理论创新，针对不同路 线做好技术储备；本体方面，组织整机和零部件企业联合定义产品并开展协同攻关，提升本体硬件水 平。系统化推进人形机器人专用芯片自主可控攻关；具身智能方 ...

Core Viewpoint - The company, Jingcheng Shares (600860.SH), primarily engages in equipment manufacturing, focusing on gas storage and transportation equipment as well as intelligent manufacturing. The company has not invested in Xiaomi Robotics or Tiangong Robotics [1]. Company Overview - The main business of the company is equipment manufacturing [1]. - Key products include gas storage and transportation equipment and intelligent manufacturing solutions [1]. Investment Activity - The company has confirmed that it has not made investments in Xiaomi Robotics or Tiangong Robotics [1].

Core Insights - The rapid evolution of robotic movement capabilities is highlighted, but understanding complex tasks remains challenging for robots [1] - The introduction of the "WoW" embodied world model by a Chinese research team represents a significant advancement in robotic intelligence [1] Group 1: Technological Advancements - The "WoW" embodied world model allows robots to simulate human-like thinking and decision-making, generating future prediction videos that align with physical laws [5] - The model enables robots to connect imagined movements with real-world execution, enhancing their interaction with the environment [5] Group 2: Data Collection and Training - The research team has collected millions of real interaction data points to ensure the world model can operate effectively in diverse real-world scenarios [8] - The model is designed to adapt to various types of robots, including humanoid and robotic arms, and can be applied across multiple settings such as homes, supermarkets, and logistics [10] Group 3: Open Access and Applications - The "WoW" model is open to global researchers and developers, facilitating broader applications and innovations in robotics [10] - It can accurately simulate extreme scenarios, such as water spilling on a computer, providing crucial data for training that is difficult to obtain through real-world testing [10]

Core Viewpoint - The article discusses the evolution of AI from "cognition" to "action," emphasizing the importance of experience-driven control in achieving practical applications in autonomous driving and robotics [5][6]. Group 1: Experience-Driven Control - The transition from traditional mathematical modeling to experience-driven control is highlighted as essential for real-world applications in complex environments [9][10]. - Experience-driven control allows AI systems to learn from historical data, enabling effective decision-making without precise mathematical models [10][11]. Group 2: Embodied Intelligence - The complexity of embodied intelligence is noted, with a focus on its higher dimensionality compared to autonomous driving, requiring advanced understanding and generalization capabilities [12][14]. - The current state of embodied intelligence is compared to the "DeepSeek moment," indicating that while significant progress has been made, a breakthrough akin to ChatGPT has not yet occurred [15][16]. Group 3: World Models - World models are identified as crucial for enabling robots to understand and interact with the physical world, serving as a foundational element for embodied intelligence [21][25]. - The article outlines three primary uses of world models: facilitating a feedback loop with the robot's brain, generating trajectory data, and integrating physical understanding into robot operations [25][26]. Group 4: Future Directions - The need for world models in the industry is emphasized, particularly for enhancing the generalization capabilities of robots in complex environments [28][31]. - The article suggests that the evolution of world models is still in its early stages, with ongoing developments aimed at improving their application in robotic training and task execution [29][30].

Core Insights - The article discusses the evolution of AI from "cognition" to "action," highlighting the transition of Tang Jian from academia to industry, particularly in the fields of autonomous driving and embodied intelligence [1][2] - Tang Jian emphasizes the importance of experience-driven control methods over traditional mathematical modeling in complex environments, suggesting that AI systems can learn from historical data to make effective decisions [4][5] - The concept of a "world model" is introduced as essential for embodied intelligence, enabling robots to understand and predict their environment, thus enhancing their operational capabilities [13][14] Summary by Sections Transition from Academia to Industry - Tang Jian, a former tenured professor, shifted focus to practical applications of AI in industry, particularly in autonomous driving and robotics [1][3] - His experience in various companies, including Didi and Midea, has informed his approach to AI-driven system control [3][6] Experience-Driven Control - The article outlines the difference between traditional control methods and experience-driven approaches, with the latter relying on data and historical experiences rather than precise mathematical models [4][5] - This experience-driven philosophy is evident in autonomous driving applications, where end-to-end control merges perception, planning, and control into a single learning process [6][7] Embodied Intelligence and World Models - Tang Jian argues that embodied intelligence presents a higher complexity than autonomous driving, requiring robots to manage multiple joints and navigate dynamic environments [7][8] - The world model is described as a critical component for robots to understand and interact with the physical world, enabling them to perform tasks that require nuanced understanding and adaptability [14][15] - The article highlights the need for a world model to facilitate the development of robots that can generalize across various tasks and environments, which is crucial for their deployment in real-world scenarios [21][22] Future Directions and Challenges - The discussion includes the potential for world models to achieve a "DeepSeek moment" in embodied intelligence, drawing parallels to breakthroughs in AI performance under limited resources [9][10] - Tang Jian acknowledges the current limitations in data and model architecture, indicating that further iterations and improvements are necessary for the field to progress [2][13] - The article concludes with the assertion that the world model is not just a technical choice but a fundamental requirement for the advancement of embodied intelligence [13][22]

Core Viewpoint - Dongtu Technology (300353) is strategically investing in the embodied robotics sector by acquiring stakes in Shenzhen Zhujidong Power Technology Co., Ltd. and Chengdu Annu Intelligent Technology Co., Ltd., and plans to lead a Series A funding round for Beijing Humanoid Robot Innovation Center Co., Ltd. [2] Group 1: Investment and Strategic Focus - Dongtu Technology's investments encompass hardware manufacturers, software model foundations, and scenario-based companies, highlighting a strong emphasis on ecological collaboration [2] - Zhujidong, founded in 2022, focuses on developing full-size humanoid robots and has attracted investments from top-tier institutions such as Alibaba, JD.com, and NIO Capital [2] - Annu Intelligent, a scenario-based company, has successfully implemented embodied intelligent robots in industrial applications, achieving commercial orders [3][4] Group 2: Technological Development and Applications - Zhujidong's humanoid robot, Oli, can autonomously perform tasks such as tennis ball recognition and retrieval, showcasing advanced motion control technology [3] - Annu Intelligent plays a crucial role in collecting vertical scene data to bridge the gap between robotic technology and practical applications [4] - Dongtu Technology aims to focus on key areas such as motion control and industrial training scenarios through its investments [4] Group 3: Research and Ecosystem Building - The Beijing Humanoid Robot Innovation Center is the first national-local collaborative platform for embodied intelligence, focusing on common technology research and ecosystem development [5] - Dongtu Technology's previous investments in the embodied intelligence sector include the launch of the Hongdao AI robot operating system, which aims to address key technological bottlenecks in domestic robotics [5][6] - The Hongdao Intewell operating system is positioned as the core of the full-stack technology for embodied intelligent robots, supporting diverse intelligent applications [6]

Group 1: Technological Innovations - The third National Skills Competition showcased advanced technologies such as a hydrogen-powered robotic dog capable of navigating complex terrains, with a static endurance of 8 hours and dynamic walking endurance of 5 hours [1] - An AI examination system designed for domestic workers can recognize over 40 dialects in China with an accuracy rate of 99%, facilitating real-time interaction [2] Group 2: Traditional Craftsmanship - The exhibition featured traditional craftsmanship, including the official glazed pottery technique, which is a national intangible cultural heritage, demonstrated by a young artisan who creates intricate pieces using specific clay and firing techniques [3] - A coffee-making demonstration highlighted the growing demand for skilled baristas, with a noted shortage in the market as coffee consumption rises among younger demographics [4] Group 3: Industry Trends - The coffee industry is experiencing rapid growth, leading to a significant demand for barista talent, with educational institutions reporting full enrollment in coffee-related programs [4] - The National Skills Competition included various exhibits showcasing high-tech innovations such as satellite return capsules and domestic chips, alongside interactive projects like AI smart glasses for CPR training [4]