Trajectory generation with rich information content

Often, trajectories for mechanical systems are generated solving some optimization problem. Common approaches include time-optimal, energy optimal, etc., motion profiles. In order to decrease mechanical wear of real plants this profiles provide, e.g., a smooth movement (rest-to-rest) in accordance with restrictions in jerk, acceleration and velocity. There exists a number of methods, to calculate for a given trajectory the plant feed forward action and to design stabilizing controllers. In case of parameter uncertainty the control law often exhibits some adaptive part. Unfortunately, smooth trajectories tend to contain insufficient excitation for adaption and/or identification. Therefore, we propose to consider some measure for the information content concerning some unknown parameters in the trajectory optimization problem.