Comparison of trajectory parametrization methods with statistical analysis for dynamic parameter identification of serial robot

This paper introduces an approach for designing exciting trajectories for parameter identification of serial robots based on a combination of Fourier Series (FS) and Schroeder Phased Harmonic Sequence (SPHS). An initial estimation of the trajectory is designed for each link using SPHS. Afterwards, the initial trajectory enable to find the initial parameters of the FS which are fed to an optimization process that finds the optimal parameters of the FS used for identification purpose. Like this, we can take the advantages of both FS and SPHS and eliminate the disadvantages of each of them. Moreover, a comparison of results between; the proposed method, original FS, and SPHS is taking place to demonstrate the effectiveness of the new approach. In this vein, a one-way analysis of variance is conducted to compare whether there are significant improvement or not. An PA10 7DoF arm robot serves as test bed for conducting experiments. Findings shows that the optimal trajectory found through the proposed approach requires less computation time compared to original FS which can be an advantage for fast and robust identification.