2026年机器人数据战先一步打响！真机数据采集系统成具身智能的石油采集器？

Core Insights - Data is becoming the core fuel for the AI era, similar to how oil was essential in the industrial age. The competition among robotics companies will increasingly revolve around data collection, generation, and application as the demand for embodied intelligence data surges [1][3]. Group 1: Importance of High-Quality Human Data - High-quality human-shaped data is crucial for embodied intelligence, as it allows robots to perform better in real-world scenarios. Unlike large language models that leverage vast amounts of internet data, embodied robots face challenges in data acquisition, requiring tailored data through real interactions or simulations [3][5]. - The industry consensus indicates that humanoid robots are likely to become the mainstream form of deployment, making the data collected from them more valuable and sustainable over the long term [5]. Group 2: Data Collection Systems - Xinghai Data Collection System: This system creates a complete closed-loop platform for data collection, management, and annotation, utilizing standardized robotic platforms to gather high-quality, multi-modal data. The Galaxea Open-World Dataset, released in August, has been downloaded 400,000 times and covers over 50 real-world scenarios, totaling 500 hours and exceeding 10TB in size [6]. - Leju Data Collection System: Comprising four core modules, this system supports two types of humanoid robots for diverse scene coverage and collaborative tasks. It has established six training sites nationwide, producing 20 million high-quality data points annually [8][9]. - Luming Robotics Data Collection System: The FastUMI Pro system focuses on high precision and efficiency, achieving a data effectiveness rate of over 95%. It aims to collect over 1 million hours of UMI data by 2026 [11][12]. - Zero Point Data Collection System: This system integrates various modal sensors to capture complete modal information, ensuring compatibility with existing algorithms and long-term data value [14][15]. - Daimeng Robotics Data Collection System: The DM-EXton2 system features force/tactile feedback, enhancing remote operation capabilities and improving data collection efficiency [17][18]. - Pasini Data Collection System: Showcasing a full-modal data collection system, it has established a leading data collection and model training base capable of producing nearly 200 million high-quality data points annually [20][21]. - Yuejiang Data Collection System: Utilizing the ATOM-M multi-modal robot, this system aims to streamline the data collection process and reduce training time significantly [23][25].