Core Viewpoint - The article discusses various advanced full-body motion capture solutions, highlighting their technical complexities and potential applications in robotics and teleoperation [1][22]. Group 1: OpenWBC Project - OpenWBC enables full-body control of the Unitree G1 robot using Apple Vision Pro for upper body teleoperation and OpenHomie for lower body movement, supporting full-body data collection [3][4]. Group 2: TWIST Project - TWIST, developed by Stanford University, allows remote control of humanoid robots through full-body motion imitation, utilizing motion capture data and reinforcement learning to enhance tracking accuracy and coordination [5][10]. Group 3: AMO Project - The AMO framework from UC San Diego combines reinforcement learning and trajectory optimization for real-time adaptive full-body control, demonstrating superior stability and expanded workspace capabilities [8][10]. Group 4: R²S² Framework - The R²S² framework focuses on developing a skill library for humanoid robots, ensuring optimal performance and robust transferability from simulation to real-world tasks [15]. Group 5: CLONE Project - The CLONE system from Beijing Institute of Technology addresses the challenges of full-body teleoperation by implementing a closed-loop correction system, achieving high fidelity in long-distance movements and complex coordinated actions [19]. Group 6: Community and Resources - The article promotes a community platform for sharing cutting-edge content, technical routes, and job opportunities in the field of embodied intelligence, aiming to foster collaboration and knowledge exchange [22][25][31].