在现场，130台2620万像素的红外相机组成矩阵，犹如科幻电影中的未来装置，以"亚毫米"级精度捕捉 着演员的每一个细微动作。"'亚毫米级'捕捉，就是捕捉精度能达到比 1 毫米还小的程度，如手指关节 的细微颤动、走路时脚踝的轻微扭转，这些肉眼难察觉的小动作都能被精准记录，让虚拟角色的动作和 真人几乎一样自然。我们的系统支持10人以上同时捕捉，包括手指关节和面部微表情，这样能大幅缩短 作品的制作周期。"动捕技术总监王祎说。 新京报讯（记者周怀宗）8月7日，位于北京怀柔区杨宋镇的动作捕捉基地正式投用，据悉，该基地是目 前亚洲最大的动捕中心。 据介绍，动作捕捉技术是一种借助先进设备，精准记录演员动作并将其转化为数字模型动画的技术，在 影视、游戏等领域应用广泛。 除了庞大的硬件规模和尖端的技术配置，基地还提供全链条服务，内设化妆间、道具库房等形成一站式 制作空间，打造覆盖影视、3A游戏、虚拟制作及非遗数字化等场景，推动跨界应用，为具身智能、无 人机定位、影视后期等提供技术支持。 杨宋镇党委宣传委员赵青介绍，作为中国影都的核心承载地，杨宋镇已构建起"创作-制作-发行"全链条 影视产业生态。未来将继续推动影视文化与科技创新 ...

Core Insights - A Beijing-based company specializing in motion capture technology for the film and sports health industries has expanded its business to train humanoid robots in football since last year, showcasing the intersection of technology and entertainment [1] - The development of motion capture equipment, initially designed for sci-fi films, has found new applications in robotics, leading to increased demand for motion data [1] - A robot football league is set to take place on June 28 in Beijing, where identical robots will compete under different software configurations, emphasizing the importance of algorithm development [2] Industry Developments - The upcoming World Humanoid Robot Sports Competition in August at Beijing's Bird's Nest will be the first comprehensive competition for humanoid robots globally, highlighting the growing interest in robotics [2] - The advancements in humanoid robotics are expected to inspire new ideas across various sectors, including youth engagement and capital markets, indicating a significant opportunity for innovation [2]

Core Viewpoint - The article highlights the innovative advancements made by the youth technology team, Yuan Ke Shi Jie, in developing a motion capture system, FZMotion, which enhances the capabilities of robots by enabling them to learn human movements and apply them in various practical scenarios [3][4][5]. Group 1: Technology Development - Yuan Ke Shi Jie has developed FZMotion, a motion capture system that accurately records human movements and converts them into data for robots to learn [3][4]. - The team has successfully implemented FZMotion in various applications, including training for the national boxing team and performances at the 2025 CCTV Spring Festival Gala [3][4]. - The technology features a "skeleton correlation algorithm" that allows it to infer true motion trajectories even when some data is obscured, significantly improving robot performance in complex environments [3][4]. Group 2: Collaboration and Innovation - The company collaborates with several universities, including Tsinghua University and Beijing Institute of Technology, to integrate academic research with practical applications [4][5]. - Yuan Ke Shi Jie has established a long-term industry-academia-research platform, facilitating the transition of academic findings into real-world applications [4][5]. - The team emphasizes a collaborative work environment, encouraging equal participation and idea sharing among all members, regardless of their position [4][5]. Group 3: Market Impact and Future Prospects - The advancements in motion capture technology are positioned to expand into various fields, including autonomous vehicles and underwater robotics, indicating a broad market potential [3][5]. - The recent policy initiatives from Beijing aim to establish the city as a global hub for embodied intelligence innovation, creating new opportunities for companies like Yuan Ke Shi Jie [5]. - The team's success in competitions and projects reflects their ability to adapt and thrive in a rapidly evolving technological landscape, showcasing the potential of youth-led innovation [4][5].

Summary of Key Points from the Conference Call Industry Overview - The conference call discusses the robotics motion capture industry, focusing on data collection methods and challenges faced by companies in this sector [1][2][4]. Core Insights and Arguments - **Data Collection Modes**: There are four primary modes of data collection in motion capture systems: 1. Real human motion capture with a physical robot, yielding 30% to 50% effective data but at a high cost. 2. Combination of real motion capture and virtual engines, allowing for 15 to 20 minutes of data collection per day at a lower cost. 3. Pure motion capture systems without physical robots, resulting in a lower effective data ratio. 4. Use of synthetic data for large-scale training, which is currently debated [2][19]. - **Data Validity Measurement**: Validity is assessed through initial human motion verification followed by robot posture validation. There is no industry standard, and the process involves multi-sensor information fusion to ensure reliability [5]. - **Data Collection Efficiency**: The efficiency of data collection is low, with 1,300 seconds of data requiring experienced motion capture experts to work continuously for several days. The main issues are the immaturity of virtual body software and challenges in interacting with real objects [6][3]. - **Cost of Data Collection**: The cost of effective data collection is approximately 300 yuan per second, with repeated data costing around 60 yuan per second. Future projections suggest costs may drop to around 200 yuan in 1-3 years, potentially below 100 yuan with student involvement [3][22]. - **Mapping Challenges**: The primary challenge in motion capture technology is the mapping of human actions to robotic actions. Current solutions often prioritize accuracy over posture, which can lead to discrepancies in execution [7][9]. - **Role of Data Factories**: Establishing data factories can significantly enhance data collection efficiency, allowing for the use of hundreds to thousands of devices to gather extensive data, which is crucial for training algorithms [10]. - **Customer Demand**: The most significant current demand comes from companies like Shiyuan, which has placed a large order of 1,000 sets, while most other companies remain in the verification stage [16]. Other Important but Overlooked Content - **Application Prioritization**: Data collection priorities are determined by customer needs and application scenarios rather than specific actions [11][12]. - **Domestic Companies' Focus**: Major domestic companies are concentrating on data collection in areas such as home services, healthcare, and rescue applications, tailoring their data collection environments accordingly [13]. - **Integration of Data Types**: The integration of motion capture data with force and tactile information is being explored to enhance the capabilities of motion capture devices [18]. - **Challenges in Mapping Solutions**: Companies face challenges in understanding human biomechanics when designing mapping solutions, often outsourcing this work to specialized motion capture firms [25]. - **Future Cost Reduction Strategies**: Cost reduction in data collection can be achieved through bulk production and collaboration with educational institutions to utilize student labor [21].

Summary of Motion Capture Technology in Robotics Industry Overview - The motion capture technology is divided into two main categories: inertial and optical systems. Inertial systems are portable but susceptible to interference, while optical systems offer high precision but come with higher costs [2][4][5]. Key Points and Arguments - **Inertial Motion Capture**: - Utilizes multi-axis sensors (e.g., nine-axis or twelve-axis) to collect motion data. It is portable and easy to operate, but suffers from cumulative errors and interference from magnetic fields [4][5][8]. - Data accuracy can be compromised in environments with Bluetooth or WiFi interference, leading to pose estimation errors and data loss [5][9]. - **Optical Motion Capture**: - Achieves sub-millimeter precision and is not affected by magnetic fields, making it suitable for high-precision applications. However, it requires a controlled environment and is sensitive to physical vibrations and lighting conditions [2][7][8]. - The cost of optical systems can be significant, with setups costing around 300,000 to 400,000 RMB [4]. - **Market Segmentation**: - The motion capture market is segmented into three tiers: - High-end market dominated by Yobeat and OptiTrack, serving major clients like Tencent and Alibaba. - Mid-tier market catering to general industrial applications and research institutions. - Niche market served by smaller companies providing specialized solutions [2][10][12]. - **Data Quality and Processing**: - Optical motion capture systems yield high data quality with an output rate of 98%-99%, while inertial systems have a slightly lower output rate of 90%-95%. Optical data often requires further processing, while robotic motion capture data is generally more straightforward [18][24]. - **Application Trends**: - The application of motion capture technology in robotics is expanding, particularly in embodied intelligence and model training. Leading companies in China are actively developing motion capture algorithms for humanoid robots [3][19][20]. Additional Important Insights - **Industry Competition**: - The competitive landscape is characterized by established players like Yobeat and OptiTrack, which have a strong presence in high-end markets, while newer entrants are gradually capturing mid-tier segments [10][13]. - **Commercial Models**: - Companies are encouraged to establish dedicated motion capture environments to enhance data collection efficiency and client satisfaction, which in turn improves profitability [14][15]. - **Future Trends**: - Data collection will become increasingly essential in robotics development, driven by the need for extensive motion data to train models effectively. This trend is expected to support the growth of the industry [21][22]. - **Optical vs. Inertial Systems**: - The future of motion capture in China is likely to remain dominated by optical systems due to their superior accuracy and lower operational costs compared to inertial systems [23][24]. This summary encapsulates the critical aspects of motion capture technology in the robotics sector, highlighting its current state, competitive dynamics, and future trends.

Summary of Human-Robot Industry Conference Call Industry Overview - The conference call focused on the human-robot industry, particularly the outlook for humanoid robots in 2024 and beyond [2][4]. Key Points and Arguments - **Market Expectations for Production**: The market currently anticipates production levels of humanoid robots to be between 5,000 and 10,000 units in 2025, with a target of 100,000 units by 2027. The ability to meet the 100,000-unit target in 2026 is a critical focus [2][4]. - **Impact of Production Rhythm**: The rhythm and scale of humanoid robot production are pivotal for market trends. A downward adjustment in production expectations could lead to a significant market correction [2][3]. - **Investment Focus on Motion Control**: Motion control is identified as a key investment area for 2025, crucial for scaling production from thousands to tens of thousands of units. The market shows high interest in motion control, but there are significant expectation gaps [5][17]. - **Differences in B2B and B2C Applications**: B2B applications prioritize cost and efficiency over universal compatibility, contrasting with B2C applications that require diverse functionalities [6][7]. - **Development Phases**: The humanoid robot industry will evolve through primary development (by original equipment manufacturers) and secondary development (by application developers), similar to mobile app development [8][11]. - **Importance of Local Partnerships**: Companies closely partnered with local manufacturers have a competitive edge in motion control algorithm development, as local firms are more likely to provide necessary API access for software development [9][10]. - **Role of Motion Capture Technology**: Motion capture technology is essential for data collection and training in the early stages of humanoid robot development, with a projected surge in demand for related equipment [13][16]. - **Market Dynamics and Supply Chain**: The supply chain's ability to meet hardware demands is critical for the humanoid robot market's growth. Regular updates on supply chain dynamics will be essential for understanding industry developments [19]. Additional Important Insights - **Anticipated Order Volume**: The demand for motion capture equipment is expected to explode, with projections indicating hundreds to thousands of data points generated daily, reflecting a robust market for training and development [14][15]. - **Investment Opportunities**: The best investment opportunities are anticipated in the secondary development sector, where tailored software applications for specific industry needs can be developed [10][12]. - **Future Trends**: The trajectory of the humanoid robot market will heavily depend on local manufacturers' capabilities and the overall supply chain's readiness to support mass production [17][18].