A two‐stage Bayesian framework for rapid dynamics identification in industrial robots
Xuechun Qiao,
Liren Yang,
Xing Liu
et al.
Abstract:Accurate dynamic models that update in real‐time are vital for industrial robots to adapt flexibly and robustly to evolving environments and tasks, enabling precise model‐based control, motion planning and disturbance estimation. However, the identification of a dynamic robot model involves multiple challenges. First, existing friction models cannot accurately characterize torque variance during prolonged robot operations. Second, traditional offline identification methods such as the least squares (LS) method… Show more
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