Core Insights - The article discusses the development of HuMI (Humanoid Manipulation Interface), a framework for humanoid robots that enables efficient data collection and skill learning without the need for cumbersome remote operation or expensive motion capture environments [1][8][21]. Group 1: HuMI System Overview - HuMI integrates portable data collection and diverse skill learning for humanoid robots, allowing operators to teach robots complex tasks efficiently using simple tracking devices [1][8]. - The system addresses the challenges of low data collection efficiency and high operator experience requirements associated with traditional remote operation methods [5][21]. Group 2: Hardware Design - The hardware design includes portable wearable devices, allowing data collection in various environments without the need to transport heavy robots [9]. - Operators use two UMI handles equipped with fisheye GoPro cameras and five HTC Ultimate VIVE trackers to capture full-body motion data [9]. Group 3: Data Collection Techniques - HuMI provides real-time inverse kinematics (IK) previews to ensure that the actions performed by the operator are physically feasible for the robot [12]. - This feature allows operators to adjust their poses in real-time, ensuring the collected data is applicable for training the robot's control systems [12]. Group 4: Algorithm Architecture - The system employs a hierarchical control strategy that integrates planning and control modules to accomplish complex full-body tasks [14][16]. - The high-level planning strategy utilizes visual input from wrist cameras to plan keypoint trajectories, while the low-level control strategy is trained through reinforcement learning [20]. Group 5: Performance Validation - HuMI successfully executed five challenging full-body tasks, achieving over 75% success rates in tasks such as proposing (kneeling), drawing a sword, throwing toys, cleaning a table, and squatting to pick up objects [17]. - The system demonstrated excellent generalization capabilities, maintaining a 70% success rate in unfamiliar environments and with unseen objects [18]. Group 6: Efficiency Improvements - HuMI significantly enhances data collection efficiency, achieving three times the throughput of traditional methods, with the ability to collect 60 valid demonstration data points in just 15 minutes for specific tasks [19]. - The system allows for the collection of complex actions that traditional methods could not accommodate due to hardware limitations [19]. Group 7: Conclusion - HuMI's core value lies in breaking the dependency on physical robots for data collection, thereby lowering the barriers and costs associated with humanoid robot data acquisition while improving learning efficiency and supporting the development of more generalized skills [21].