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System Identification is the process of collecting input-output data from a real system to infer unknown parameters of a simulation model (such as friction coefficients, joint damping, and contact stiffness); compared with domain randomization, it can yield point estimates of parameters closer to reality, but it relies on high-quality measurement data and additional experimental procedures.
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11/3/2026
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