Trust-Region Neural Moving Horizon Estimation for Robots: Efficient Training and Superior Performance

The author proposes a trust-region policy optimization method for training NeuroMHE, leveraging the efficient reuse of computation to calculate the MHE Hessian. This approach enhances training efficiency and robustness while achieving superior performance in disturbance estimation.