Human body model: 206 joints and 700 muscles for MuJoCo (MS-Human-700) (lnsgroup.cc)

The MS-Human-700 project has unveiled a sophisticated human body model designed to enhance our understanding of musculoskeletal functions through advanced simulations. This model incorporates 90 segments, 206 joints, and 700 muscles, creating a comprehensive framework for research across various disciplines including brain-body interactions, robotics, and sports. The initiative integrates high-fidelity physiological simulations with state-of-the-art reinforcement learning techniques, promising significant advancements in embodied intelligence and medical applications. Key innovations of the MS-Human-700 project include its DynSyn system, which optimizes policy learning for overactuated systems, and MPC2, which employs hierarchical model predictive control for efficient motion planning. Additionally, SoftFoot enhances locomotion realism through advanced deformable contact dynamics, while QFlex addresses exploration challenges in complex control environments. The project also introduces MoVLR, a vision-language model that simplifies musculoskeletal control through intuitive reward specification. Collectively, these components represent a pivotal step forward in digital human simulation, offering valuable tools for researchers and practitioners in AI and machine learning.