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In this paper, we present the results and implications of our experimental study into the parameter identification and the position error modelling of a Motoman SK 120 robot manipulator for kinematic calibration. The true values of the parameters and the coefficients of the error model are estimated, in the least-squares sense, from the position data of 85 identification configurations of the manipulator measured by a high precision laser tracking system. The proposed error model is utilised to calculate the expected position errors for an exemplary Cartesian space trajectory. These errors are then corrected using a first order approximation of the inverse kinematic model. The results prove that the established model is accurate enough to represent position error of the manipulator without needing further experimental position data. This work contributes to previously published work from the point of view of being a simple and systematic approach to the self-calibration of robotics systems with minimum experimental data.