【环球时报记者 杨沙沙 王冬 环球时报驻美国特约记者 卓然】 编者的话： 1月6日至9日，位于世界科技舞台"C位"的2026年国际消费电子展（CES）在美国拉 斯维加斯举行，本届CES以"Smarter AI for All"为主题，汇聚4500余家国际科技企业，展示全球最具未来感的科技革命与商业创新。各种人工智能（AI）终 端、人形机器人、无人出租车令人目不暇接……今年的CES将有哪些令人兴奋的杰出创新与巧妙升级？中国企业在其中扮演什么角色？《环球时报》记者采 访了多位参展方代表及业内人士。 " 中企占据了机器人展区 " 一位"机械舞者"头顶牛仔帽，身穿西服马甲，舞步丝滑流畅——1月6日，在近一年前将人形机器人"搬上春晚"的宇树科技在CES现场不仅开起了"机器人舞 会"，还办起格斗擂台赛，外国观众纷纷拿起手机驻足拍照。中国人形机器人企业加速进化公司带来机器人足球赛冠军——Booster K1机器人矩阵，数十台 机器人通过集体扭头、挥手、齐舞乃至演绎非遗舞狮，以流畅动作与观众互动。今年参展的中国企业展现出人工智能（AI）与硬件的深度融合，以及在具 身智能、AI眼镜等前沿领域的集群式技术突破。 展会上，包括宇树 ...

这一战略转型的背景是Tesla主营业务面临压力。公司周五报告称，2025年全年汽车销量下降9%，第四 季度下降16%，年度销量落后于中国的比亚迪。在电动汽车销售放缓之际，马斯克试图通过转向 Robotaxi和人形机器人来重振投资者信心。马斯克的新薪酬方案更是将目标设定为在10年内让Tesla市值 达到8.5万亿美元，并售出至少100万台机器人。 尽管资本市场对机器人产业的长期前景保持关注，但Tesla内部及行业专家对Optimus的实用性存在分 歧。一方面，工程师在制造具备人类感知力和灵巧度的机械手方面遭遇瓶颈；另一方面，部分内部员工 质疑在工厂制造等常规业务中，人形机器人是否真比专用自动化设备更具效率。 远程操控与"幕后"真实状态 虽然Optimus已成为Tesla公司活动中的常客，甚至在《创：战神》（Tron: Ares）的好莱坞首映式上亮 相，但在光鲜的演示背后，该项目仍处于高度依赖人工辅助的开发阶段。 据知情人士向华尔街日报透露，在去年的演示活动现场，每一个与人互动的机器人背后都需要多名工程 师的实时监控与操作：一人穿戴设备进行远程操控，一人通过笔记本电脑监控，其他人则在现场确保机 器人的物理稳定性。 ...

Core Insights - The rise of humanoid robots has become a significant trend in the tech industry, with automotive companies increasingly investing in humanoid robot development as a new growth avenue amidst slowing market growth in traditional automotive sectors [2][20][26] - Tesla's humanoid robot, Optimus, is positioned as a key product for the company's future, with expectations that it will contribute significantly to Tesla's overall value [3][4][20] - Chinese automakers, including Xpeng and BYD, are also making strides in humanoid robotics, with Xpeng's IRON robot showcasing advanced capabilities and aiming for mass production by the end of 2026 [8][10][26] Industry Trends - The automotive sector is witnessing a collective push towards humanoid robotics, with nearly all major car manufacturers increasing their involvement in this field [2][7] - Companies are adopting various strategies, including full-stack self-research and partnerships with established robotics firms, to accelerate their entry into the humanoid robot market [10][11] - The market is expected to see a significant increase in humanoid robot deployment, with projections suggesting a market size of $5 trillion by 2050 [27] Technological Challenges - The development of humanoid robots faces significant technical hurdles, particularly in achieving stability and functionality in real-world environments [12][13][15] - Key challenges include the complexity of creating dexterous hands, stable locomotion, and advanced AI capabilities for real-time decision-making [14][16][17] - Current production methods are still largely manual, limiting the scalability of humanoid robot manufacturing [18] Market Dynamics - The entry of automotive companies into humanoid robotics is seen as a strategic move to diversify and mitigate risks associated with traditional automotive business cycles [20][21] - The overlap in technology and components between electric vehicles and humanoid robots provides automotive companies with a competitive advantage in this new market [21][22] - The industry is at a critical juncture, with the potential for significant breakthroughs or the risk of stagnation due to unresolved challenges [27]

新华财经上海12月30日电（魏雨田）12月30日，机器人板块迎来强势表现。新华财经数据显示，中证机 器人指数当日上涨3.31%，步科股份、伟创电气、新时达等多只概念股涨停。弘毅远方甄选混合基金经 理王哲宇认为，机器人板块上涨的核心驱动因素在于产业正从技术研发阶段加速迈向商业化验证，国内 主机厂的技术突破与海外特斯拉供应链的积极进展形成共振，市场对机器人作为AI物理核心载体的长 期价值预期也因此显著提升。 编辑：谈瑞 具体来看，王哲宇表示，这一趋势由国内外多重利好因素共同推动，国内方面，作为国内足式机器人领 域"杭州六小龙"之一的杭州云深处科技股份有限公司已正式启动上市辅导，展望未来，预计明年将有更 多机器人产业链相关厂商登陆资本市场，这一上市潮有望带动全行业资本开支的提升，从而进一步催化 相关供应链的发展；海外方面，特斯拉Optimus（擎天柱）的量产方案正逐步清晰，目前已进入设计冻 结阶段，供应链反馈普遍积极，市场普遍预计其主要零部件的定点工作将于年初完成，其量产时间与规 模均有望超出市场此前的预期。 从市场结构来看，王哲宇认为，当前机器人板块的成交额占比处于历史低位，赛道拥挤度较2025年第二 季度和第三 ...

Core Insights - The humanoid robot sector is gaining momentum globally, driven significantly by Elon Musk and Tesla's efforts with the Optimus robot, which has seen incremental developments since its concept reveal in 2021 [1][2] - Tesla's ambitious production goals for Optimus have faced setbacks, with the announcement of a production target of 5,000 units in 2025 being contradicted by reports of insufficient capacity [1][2] - The divergence in market focus between Tesla's C-end (consumer) applications and domestic players' B-end (business) strategies highlights differing approaches in the humanoid robot landscape [3][4] Market Dynamics - Tesla's Optimus aims to serve both industrial and consumer markets, with recent demonstrations showcasing its capabilities in home settings [2][3] - Domestic players, such as UTree and UBTECH, primarily target B-end applications, focusing on industrial orders and public service demonstrations [3][5] - The shift in consumer demographics in the U.S. towards tech-savvy individuals may create a favorable market for consumer-oriented humanoid robots [4][5] Technical Challenges - The delays in Optimus's production reflect ongoing technical challenges, particularly in developing a functional and standardized dexterous hand [7][8] - Competitors like XPeng have made strides in dexterous hand technology, highlighting Tesla's struggles in this area [8] - The need for effective AI and data collection methods remains a significant hurdle for both Tesla and domestic players [9] Cost Considerations - While Tesla has substantial resources, domestic players must navigate cost-performance balance to achieve profitability [10][11] - The humanoid robot sector has seen significant investment activity, with over 140 financing events totaling nearly 20 billion yuan in the first half of the year [10] - Collaborations with established suppliers and leveraging domestic supply chains are crucial for cost management and technological advancement [11][12] Industry Outlook - Tesla's Optimus project serves as a benchmark for supply chain integration in the humanoid robot industry, influencing upstream suppliers and market perceptions [12] - The success of domestic humanoid robot manufacturers will depend on their ability to meet market demands and provide effective solutions [12]

Core Viewpoint - Tesla is shifting to a single, large end-to-end neural network that directly generates control actions from pixel and sensor data, eliminating explicit perception modules [1][34]. Group 1: Reasons for Transition to End-to-End Neural Networks - Integrating human values (like driving smoothness and risk assessment) into code is extremely challenging [3]. - Poor interface definitions between traditional perception, prediction, and planning can lead to information loss [4]. - The end-to-end approach is easier to scale for handling long-tail problems in the real world [5]. - It allows for homogeneous computation with deterministic latency, which is crucial for real-time systems [6]. Group 2: Challenges in Learning "Pixel to Control" - The primary challenges include the curse of dimensionality, interpretability and safety guarantees, and evaluation [7][8][9]. - The input context can be extensive, with a 30-second window potentially reaching 2 billion tokens [10][49]. - Tesla leverages its vast fleet data to extract valuable corner case data through complex, trigger-based data collection methods [11][51][56]. Group 3: Solutions to Challenges - For the curse of dimensionality, Tesla refines its extensive driving data to ensure the right correlations are captured [51][56]. - Interpretability is addressed by prompting the end-to-end model to predict various auxiliary outputs for debugging and safety assurance [12][60]. - Evaluation challenges are tackled by creating a neural network-based world simulator that can generate consistent video streams from multiple cameras [19][79]. Group 4: Future Developments - The next step involves the Cyber Cab, a next-generation vehicle designed specifically for robotaxi services, utilizing the same neural network technology [25][83]. - The technology developed for autonomous driving is also being adapted for humanoid robots, such as Optimus [26][86].

Core Insights - The competition between Elon Musk's Tesla and Brett Adcock's Figure in the humanoid robot sector highlights two distinct approaches to realizing the future of robotics [4][28] - Figure's recent product launch, Figure 03, has gained significant public attention, contrasting with Tesla's more reserved approach to showcasing its Optimus robot [2][28] Company Overview - Tesla and Figure entered the humanoid robot market around the same time, with Musk announcing the Tesla Bot (later named Optimus) in August 2021 and Adcock founding Figure AI shortly thereafter [5][6] - Both companies have made significant strides in humanoid robot development, with Tesla focusing on engineering and system building, while Figure emphasizes public engagement and practical demonstrations [4][24] Product Development Timeline - Tesla's Optimus has seen several iterations, including the Bumble C prototype in 2022 and the Gen1 and Gen2 models in 2023, with a focus on refining its capabilities [6][7] - Figure has rapidly progressed with its robots, launching Figure 01 in March 2023 and Figure 02 in August 2024, showcasing practical applications in everyday settings [6][9] Public Perception and Marketing - Figure's marketing strategy involves demonstrating robots in relatable home environments, creating a tangible sense of how robots can integrate into daily life, while Tesla's focus remains on technical specifications and engineering challenges [3][4] - The contrasting narratives have led to Figure capturing more public attention, while Tesla's Optimus is perceived as a more internal project lacking public visibility [3][14] Future Projections - Musk envisions a future where humanoid robots could outnumber humans significantly, with production targets suggesting Tesla could manufacture up to 100 million units annually [15][28] - However, challenges in production, supply chain issues, and team instability have led to delays in Tesla's robot rollout, raising questions about its ability to meet these ambitious goals [19][26] Strategic Focus - Figure's singular focus on humanoid robots allows it to allocate all resources towards this goal, while Tesla's broader responsibilities as an automotive and energy company may hinder its agility in the robotics space [20][25] - The competition reflects a generational shift, with Adcock embodying a more agile, startup mentality compared to Musk's established corporate approach [27][28]

Core Insights - The Chinese humanoid robot industry is rapidly advancing, leveraging manufacturing advantages and significantly reducing costs, making robots more accessible to consumers [1][2][4] - While China excels in hardware production and cost control, the U.S. maintains an edge in software ecosystems and AI capabilities, particularly in developing intelligent robots that can understand and interact with their environment [10][11][59] - The competition between Chinese and American humanoid robots is intensifying, with both sides focusing on different aspects of development: China on market penetration and cost reduction, and the U.S. on advanced AI and software integration [13][15][60] Industry Overview - The humanoid robot market is projected to experience explosive growth, with estimates suggesting that the global market could reach 1.1 trillion yuan by 2035, and the Chinese market alone could achieve 300 billion yuan [23][24] - As of mid-2025, over 220 humanoid robot companies exist globally, with Chinese firms accounting for more than half of this total [27] - The Chinese humanoid robot sector is witnessing a surge in enterprise registrations, with over 105 new companies established in the first half of 2025, reflecting a significant shift towards commercialization [42] Technological Developments - Chinese companies are focusing on specific industrial applications for humanoid robots, such as quality inspection in automotive manufacturing and precision tasks in agriculture [5][6][60] - Despite advancements, Chinese humanoid robots still face challenges in basic capabilities like motion control and autonomy, indicating a need for further technological development [31][34] - The U.S. is making strides in creating humanoid robots with advanced AI capabilities, such as Tesla's Optimus, which is designed to perform complex tasks and adapt to various environments [38][50][55] Market Dynamics - The competition is characterized by a divergence in strategies: Chinese firms prioritize cost-effective production and market capture, while American firms emphasize software innovation and AI integration [15][62] - Significant investments are flowing into the humanoid robot sector, with over 14 billion yuan raised globally in the first half of 2025, and Chinese companies securing a substantial portion of this funding [24][66] - The regional concentration of humanoid robot companies is notable, with the Yangtze River Delta region housing a significant share of enterprises, indicating a trend towards industrial clustering [43] Future Outlook - The humanoid robot industry is at a critical juncture, transitioning from basic mobility to functional task execution, with the potential for widespread application in various sectors due to labor shortages in aging societies [37][66] - The ultimate competition will hinge on the development of "embodied intelligence," which combines advanced AI with humanoid robotics, determining which country can produce robots that not only move but also think and adapt [19][64]

Core Viewpoint - Despite significant investments from venture capital firms and large tech companies, humanoid robots still struggle to achieve dexterity, which is essential for performing tasks in human environments [2][3][4]. Group 1: Historical Context of Humanoid Robots - The concept of humanoid robots has been explored for over 65 years, with early developments including a computer-controlled robotic arm capable of stacking blocks in 1961 [3]. - The evolution of humanoid robots has seen contributions from various institutions, including WABOT-1 from Waseda University in the 1970s and Honda's ASIMO in 2000 [11][12]. Group 2: Current State and Future Predictions - Humanoid robots are currently in the early stages of development, with Gartner indicating they have not yet reached their peak hype [4]. - Companies like Tesla and Figure are optimistic about the economic potential of humanoid robots, with predictions of creating trillions in revenue [9][10]. Group 3: Challenges in Dexterity - Achieving human-level dexterity in humanoid robots remains a significant challenge, as current robotic hands lack the necessary finesse and adaptability for a wide range of tasks [23][24]. - Existing methods for training robots often rely on visual demonstrations, which do not adequately capture the tactile feedback necessary for dexterous manipulation [27][28]. Group 4: Learning Approaches - The industry has seen a shift towards end-to-end learning methods, where robots learn from observing human actions, but this approach has limitations due to the lack of tactile feedback and precision [30][31]. - Successful applications of end-to-end learning in other fields, such as speech recognition and image labeling, highlight the importance of pre-processing and human-like structures in achieving effective learning outcomes [49][50]. Group 5: Importance of Tactile Feedback - Human dexterity is heavily reliant on rich tactile feedback, which current humanoid robots do not possess, leading to challenges in replicating human-like manipulation [51][52]. - The complexity of human touch perception and the integration of multiple body parts in dexterous tasks further complicate the development of humanoid robots capable of similar actions [52].

Core Viewpoint - Elon Musk emphasized that Tesla is fully committed to scaling the Optimus project, defining it as the most important product in the company's history, with expectations that it will account for 80% of the company's future value [2][6]. Group 1: Production Timeline and Goals - Tesla aims for internal limited production and testing of thousands of Optimus units by 2025, ramping up to 50,000-100,000 units for external sales in 2026, and targeting an annual production of 1 million units within five years [2]. - The current supply chain for Optimus is based on the design of Optimus V2, with actuators and sensors each accounting for approximately 30% of material costs [4]. Group 2: Supply Chain and Component Suppliers - The supply chain for Optimus includes Tier 1 suppliers such as Sanhua Intelligent Controls and Top Group for actuators, and Mingzhi Electric and Zhaowei Electromechanical for dexterous hands [7]. - Key component suppliers include Shuanghuan Transmission and Lide Harmony for reducers, Best for lead screws, and Rongtai Health for insulation parts [7]. - International Tier 1 suppliers include Amphenol for cables, TE Connectivity for six-dimensional torque sensors, and THK for lead screws [8]. Group 3: Challenges and Development Needs - Current challenges for Optimus include hardware issues such as overload and overheating of joint motors, insufficient dexterity and load capacity of dexterous hands, and the lifespan of transmission components [10]. - There is a need for improved compatibility between hardware and software, particularly in complex dynamic environments and multi-task coordination [10]. Group 4: Thermal Management Solutions - The thermal management system for Optimus V3 is similar to that of electric vehicles, focusing on the management of key components like batteries and motors [11]. - Sanhua Intelligent Controls is developing liquid cooling modules for Optimus, leveraging its experience in electric vehicle thermal management to address overheating issues in robotic joints [13]. - Sanhua plans to deliver approximately 2,000 actuators to Tesla by Q3 2025, with an annual order forecast of 5,000-10,000 units [13]. Group 5: Industry Trends and Future Outlook - Domestic suppliers are increasing investments to meet the demand for high-performance, miniaturized thermal management components for robots [14]. - The year 2025 is anticipated to be a pivotal year for humanoid robot mass production, with 2026 expected to be a critical turning point for the industry landscape [14]. - The upcoming iTherM 2025 conference will address advanced thermal management technologies and materials relevant to humanoid robots [15].