Core Insights - The core technology for humanoid robots is motion control, which is essential for dynamic gait, precise operations, and environmental adaptability [1] - The humanoid robot industry faces both opportunities and challenges, with potential applications in various sectors such as industrial automation, medical rehabilitation, and education [1] - Precise complex motion control technology is fundamental for the widespread application of humanoid robots [2] Industry Overview - Humanoid robots are characterized by human-like form and functions, and their development is driven by advancements in robotics control and AI technology [1] - The industry is experiencing rapid evolution due to continuous influx of capital and talent, although large-scale commercialization still faces technical, economic, and social challenges [1] Motion Control Techniques - Motion control for humanoid robots can be categorized into model-based control and data-driven control, each with unique advantages [3] - Model-based control relies on accurate modeling and manual parameter adjustments, while data-driven control allows robots to learn motion strategies from experience [3] - A hybrid control approach combines both methods to enhance adaptability and robustness, improving the operational capabilities of humanoid robots [3] Key Players and Beneficiaries - Leading companies like Tesla with Optimus, Yushun with G1, and Boston Dynamics with Atlas demonstrate strong motion control capabilities [4] - The development of motion control software algorithms is typically conducted in-house by robot manufacturers, while hardware components may be sourced from third-party suppliers [4] - Training-related hardware such as motion capture devices and simulation software tools are often provided by third-party vendors or open-source platforms [4]

Core Viewpoint - The article discusses the current state and future potential of humanoid robots in China, highlighting the gap between public perception and technological reality, as well as the diverse strategies adopted by leading companies in the industry [2][3]. Group 1: Industry Development - The humanoid robot industry in China has significant milestones, such as the 2025 Spring Festival Gala performance and the recent Beijing Yizhuang Marathon, which showcased the capabilities and limitations of humanoid robots [2][3]. - A field study of nine leading companies in Shenzhen revealed a lack of consensus on technology routes and application scenarios, indicating a transitional phase from laboratory to industrialization [3]. Group 2: Key Divergence Points - The industry faces several critical questions, including whether humanoid robots need legs, faces, and how they perceive the environment [4][12][17]. - Companies are divided into "bipedal" and "wheeled" factions, with each focusing on different capabilities and applications based on their technological strengths [6][7]. Group 3: Technical Challenges - Bipedal robots face significant technical challenges, including the need for complex joint coordination and energy consumption, while wheeled robots are more stable and cost-effective for industrial applications [7][8]. - The perception and interaction capabilities of humanoid robots vary, with some companies prioritizing industrial functionality over human-like features to avoid ethical concerns [13][14]. Group 4: Data and Training - The competition in the humanoid robot industry is increasingly centered around data acquisition for training AI models, with companies employing various strategies to gather real, simulated, and internet data [28][29]. - Companies like Digital Huaxia are investing in data collection centers to create realistic training environments, while others focus on simulation data to reduce costs and accelerate learning [28][30]. Group 5: Market Applications - Humanoid robots are being explored for various applications, including industrial manufacturing, logistics, retail, and education, but the timeline for widespread adoption remains uncertain [33][34]. - The industry is currently prioritizing standardized industrial applications before moving into more complex environments like homes [34][35]. Group 6: Commercialization Challenges - The humanoid robot sector struggles with finding clear commercialization paths, with many companies still reliant on investment rather than sustainable revenue [36][38]. - The transition to mass production is hindered by inconsistent product performance and the need for precise hardware and software integration [40]. Group 7: Public Perception and Future Outlook - Events like the Yizhuang Marathon have sparked debate about the viability of humanoid robots, with some viewing the failures as indicative of a bubble in the industry [42][43]. - Despite challenges, there is a recognition of the progress made in humanoid robotics, and industry insiders advocate for a balanced view that acknowledges both the potential and current limitations of the technology [43].

ReadMultiplex平台发布的人形机器人综述指出，全球机器人技术正在经历重要变革，人形机器人正逐步进入高收入家庭和工业生产领域。这类机器人具备 家务协助、儿童教育、老人看护等功能，同时也能缓解劳动力短缺问题，推动制造业和服务业的转型升级。 市场研究显示，人形机器人产业具有巨大发展潜力。预计到2030年，全球市场规模可能达到24万亿美元，其中家庭应用和工业应用将各占约50%的份额。 这一发展趋势不仅反映了技术进步，也预示着社会生产生活方式的深刻变革。 01.为什么人形机器人是最佳选择？ 我们的世界，从门把手到楼梯、从汽车仪表盘到工厂工作站，都是为人类体型、灵活性和动作设计的，这使得人形机器人相比轮式或固定臂机器人能无缝 适应现有环境，无需昂贵的基础设施改造。 人形机器人凭借其独特优势脱颖而出：它们能直接融入基于人体工程学设计的环境，如椅子、桌子、梯子，操作按钮、杠杆、触摸屏，并通过双足移动穿 越楼梯、狭窄空间及非结构化环境，如家庭、仓库和建筑工地。 例如，特斯拉Optimus和波士顿动力Atlas的机器人手部可使用螺丝刀、键盘、钻头等人类工具，开启门阀或处理脆弱物体，无需定制末端执行器。其拟人 化设计，如 ...

Core Viewpoint - The discussion surrounding the Yushu H1 robot's ability to perform complex gymnastic movements while struggling in a half marathon highlights the "impossible triangle" of hardware, algorithms, and scenarios in the humanoid robotics field [2] Group 1: Hardware Design Challenges - The Yushu H1 features a joint motor torque density of 230Nm/kg and a real-time control system with millisecond response speed, allowing it to switch its center of gravity in 0.5 seconds, prioritizing instantaneous power output [3] - However, this design leads to a significant power consumption of 300W per joint during dynamic activities, which is much higher than during normal walking [3] - During a marathon at a speed of 6km/h, the robot requires over 500W of total heat dissipation, exceeding its passive cooling system's capacity, resulting in knee joint temperatures exceeding 80°C after one hour, causing a 23% decrease in torque precision [4] Group 2: Algorithmic Layers - The VSLAM (Visual Simultaneous Localization and Mapping) system developed by Yushu allows for environmental perception at 60 frames per second, with a gait generator trained through reinforcement learning, achieving a reaction delay of only 80ms when avoiding obstacles, close to human spinal reflex speeds [5] - For marathon running, an energy consumption model must be established, requiring the robot to keep energy use below 238Wh per kilometer to cover 21 kilometers with a total battery capacity of 5kWh [7] - If the path planning algorithm is not optimized, actual endurance may drop to 15 kilometers, and the robot's "5-minute battery swap" plan results in loss of motion memory, effectively resetting its learning model every 5 kilometers [7] Group 3: Differences in Participants - The Yushu H1 robot participating in the marathon was modified by a client and did not use the original factory algorithm, which is based on 100,000 hours of simulation training with a foot pressure sensor error compensation frequency of 200Hz [8] - In contrast, the third-party algorithm used had a sensor calibration frequency of only 50Hz, leading to a fourfold increase in error accumulation during continuous running, explaining why the robot could stand on one leg for over 30 minutes in the lab but struggled in the race [8] Group 4: Industry Insights - The trend towards performance specialization is evident, with Tian Gong Ultra reducing weight by 8kg and lowering energy consumption by 15% for inspection and logistics, while Yushu H1 retains a 12-degree-of-freedom dexterous hand for flexibility in rescue and service scenarios [9] - Technological breakthroughs are being pursued, such as Boston Dynamics' Atlas experimenting with liquid metal cooling systems to reduce joint operating temperatures by 40%, and Tesla's Optimus improving energy efficiency through silicon carbide inverters [9] - Over the next five years, humanoid robots are expected to achieve breakthroughs in both gymnastics and marathon capabilities as solid-state battery energy density surpasses 400Wh/kg [9] Conclusion - The evolution of technology is a necessary path, as seen in the transition from laboratory demonstrations to practical applications in humanoid robotics, emphasizing the importance of algorithm optimization for performance leaps [10]