Siemens has outlined how system simulation can address the interconnected challenges of humanoid robot development. Using Simcenter Amesim, its approach brings mechanical, electrical, control, and energy systems into a virtual digital twin to study locomotion, actuator configurations, manipulation, battery requirements, thermal behavior, and autonomous navigation.
The company also describes using physics-based simulation to generate synthetic data for AI training and support sim-to-real transfer. By varying conditions such as slopes, uneven terrain, and surface friction, the approach aims to help robots adapt to environmental uncertainties before physical deployment.
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