Optimal motion planning for robot's inertial parameters identification

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Abstract
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 author presents an improvement of a previous method for generating exciting identification trajectories in order to minimize the effect of noise and error modeling on the LS solution. Using nonlinear optimization techniques and the usual robot trajectory generator, the condition number of a matrix W obtained from the energy model is minimized. An example of a three-degree-of-freedom robot is presented. The advantages of the proposed method compared with the previous method include the use of any classical industrial robot trajectory generator, a one-step solution using efficient nonlinear programming which makes it possible to take into account the interpolation, the joint velocity limits as bound constraints, and the joint position limits as nonlinear constraints, and a short time trajectory. The optimal trajectory is easy to generate and easy to implement on industrial robots.

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