Exciting trajectories for the identification of base inertial parameters of robots

A common way to identify the inertial parameters of robots is to use a linear model in relation to the parameters and standard least squares (LS) techniques. The authors present a method to generate exciting identification trajectories in order to minimize the effect of noise and error modeling on the LS solution. Using nonlinear optimization techniques, the condition number of a matrix W obtained from the energy model is minimized and the scaling of its terms is carried out. An example of a 3 degree of freedom robot is presented