In this paper, we concentrate on the design of optimal excitation trajectories, a novel parameter optimization algorithm is proposed by taking advantages of two types of optimization objective functions. On the basis of the above-mentioned, the Lie-theory-based identification methodology of serial robots is introduced to demonstrate the impact of excitation trajectory optimization. Whereafter, we have conducted an experimental analysis on the performance of three different optimization methods. The results reveal that the proposed approach can significantly decrease the computation time required for trajectory optimization while maintaining the robust identification.
