System identification (sysid) is the process of finding the physical parameters that make a simulation match reality. If you're training an RL locomotion policy in simulation, the accuracy of your motor model directly affects how well the policy transfers to the real robot.
A recent git commit by @kevin_zakka added a sysid toolbox to MuJoCo which automates this process: you provide recorded motor data and a MuJoCo model, and it optimizes the model parameters to minimize the difference between simulated and real trajectories.
For my @RobStride_com RS02 QDD motors (17 Nm peak, 7.75:1 gear), I built a Rust tool that sends multi-sine torque excitation at 1 kHz and records position/velocity feedback. I then feed this data into MuJoCo's sysid optimizer.
La primera película de Toy Story (1995) requirió 800.000 horas de máquina usando un grupo de 117 computadoras y 110 empleados.
La pelicula tiene 114.240 cuadrados de animación. Pixar podía renderizar menos de 30 segundos de la película por día.
Hoy cuanto demorarían? 🤔