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==== Virtual before Testing Before Physical Implementation in Humanoid Robotics ====Use ISAAC NVIDIA's Isaac Sim and Isaac Gym, alongside other simulators, form a crucial foundation for designing and testing humanoid robots virtually. Insights and suggestions from experts working with these tools are captured below. ===== Isaac-Based Simulators and Frameworks ===== ====== Isaac Sim ====== IDE Experience: Provides a comprehensive, if complex, simulation environment. PhysX Engine: Utilizes the PhysX engine to test your handle both contact and joint constraints, though Isaac Sim currently does not fully expose closed-loop constraint capabilities. Joint Constraints: Supports maximal coordinate systems, which include joint constraints that are common in articulated robots. Virtual Sensors: Allows the simulation of perception with virtual cameras and LiDARs, providing policy training inputs rendered with NVIDIA RTX. ====== Isaac Gym ======Reinforcement Learning Training: Enables parallel environments for fast policy training. PHC Approach: Integrates AMP for real-time pose control, making it easier to teach new skills. Gait Optimization Issues: While 17-DOF walking tasks work well, gait reward optimization needs refinement for more complex tasks. Closed-Loop Articulation: Belt-driven mechanisms provide a viable alternative for certain closed-loop designs under various simulated conditions . ====== Orbit Framework ====== Unified Training Framework: Integrates Isaac Sim and Isaac Gym for modular and consistent policy validation. OmniIsaacGymEnvs: Offers predefined tasks like walking and standing. ====== Omniverse Isaac Gym ====== Shift in Development: NVIDIA is consolidating Isaac Gym into Isaac Sim through Omniverse, providing the best of both worlds. Challenges: Demands powerful NVIDIA GPUs, potentially limiting some development workflows. ===== External Tools and Comparative Platforms ===== ====== Legged Gym ====== A repository showcasing the state-of-the-art in legged robot training.- MuJoCo (MJX): Offers a lightweight open-source alternative, supporting maximal coordinate constraints and easier to refine your work with.- VSim: Claims to be 10x faster than other simulators.- ManiSkill/Sapien: Provides tactile simulation and visual-based policy training that is up to 100x faster than Isaac Sim. == Best Practices for Virtual Testing ==- Incremental Complexity: Start simple and build up to more complex environments and tasks.- Cross-Simulator Validation: Validate robotmodels across simulators (e.g., Isaac and MuJoCo) to ensure robustness.- Incorporate Real-World Fidelity: Include sensor noise and imperfections for better policy generalization.- Optimize Resources: - Use Azure's mechanics A100 GPUs for Isaac training. - Capture real-world data to refine virtual training.  By understanding the nuances and strengths of each simulator, developers can refine their humanoid robots effectively. Using Isaac Sim, Isaac Gym, and complementary tools, a robust simulation approach ensures smooth virtual-to-physical transferability while reducing development time and electronicscosts.