To identify the friction model parameters of a modular joint， an off-line identification method that compensates the joint friction is proposed. First， the structure and control system of the modular joint are presented， and the dynamic model of the joint is established. Second， the LuGre friction model is developed. The grey wolf algorithm and piecewise least-square algorithm with a pseudo random sequence are then used to identify the respective model parameters. The results of two methods are compared and analyzed， and a feed-forward compensation algorithm based on the LuGre friction model is designed and verified experimentally. The experimental results indicate that compared with the piecewise least-square method， the identification accuracy of the grey wolf algorithm improved by 19.2%； the joint velocity tracking error decreased from 0.295 （°）/s to 0.183 （°）/s when the given velocity signal was a sine wave with an amplitude of 1 （°）/s and a frequency of 10 Hz； and the velocity loop bandwidth increased from 12 Hz to 18 Hz after friction compensation. Several experiments are repeated， and the identified data exhibit a high repeatability， which verifies the suitability of the proposed method. The proposed feed-forward friction compensation algorithm can be used to improve the dynamic performance of the joint control system.