On-line parameter identification of a cart by mobile manipulation pushing

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In this paper, a model identification method for unknown parameters of a non-holonomic cart has been developed. By interactions between a mobile manipulator and the cart, the sensory information is collected to estimate the model parameters of the cart. Since the raw data are contaminated by noise that cannot be modeled statistically, a wavelet based least square method (LSM) is proposed to estimate these parameters for the cart. The raw signal is decomposed into certain bandwidths to generate a series of new signals, which are used to estimate the parameters. The new signal, which has the minimal estimation residual in the least square sense, is adopted as the best estimation. The error convergence of the estimation approach is given. The experimental results indicate that the estimation accuracy can be significantly improved by the use of the proposed method. © 2003 Elsevier B.V. All rights reserved.

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Robotics and Autonomous Systems