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Why Simulation Which Simulation Engine Should I Use? MuJoCo MuJoCo Warp Isaac Sim Isaac Lab How Isaac Lab 3.0 Relates to Isaac Sim and Newton Modern GPU-Accelerated Physics for Robotics Newton Other Simulation Engines Conclusion
Why Simulation
Figure 1: Humanoid robot locomotion simulation. The robot's pose is represented by tracked body keypoints (green markers), while successive robot instances illustrate its movement through time. Directional arrows indicate commanded motion, demonstrating the use of a physics-based simulation environment for training and evaluating robot locomotion and control policies.
The primary challenge in building physical AI systems is data availability. Large language models (LLMs) and vision-language models (VLMs) can be trained on internet-scale datasets, but robotics and physical AI systems do not have the same advantage. To train a physical AI system, a robot must learn the consequences of interacting with the physical world. For example, it needs to understand what happens when a cup slips, a cable bends, or a gripper contacts an object at the wrong angle.
