Alexander Reiter

Alexander Reiter describes optimal path and trajectory planning for serial robots in general, and rigorously treats the challenging application of path tracking for kinematically redundant manipulators therein in particular. This is facilitated by resolving both the path tracking task and the optimal inverse kinematics problem simultaneously. Furthermore, the author presents methods for fast computation of approximate optimal solutions to planning problems with changing parameters. With an optimal solution to a nominal problem, an iterative process based on parametric sensitivities is applied to rapidly obtain an approximate solution.About the Author:Dr. Alexander Reiter is a senior scientist at the Institute of Robotics of the Johannes Kepler University (JKU) Linz, Austria. His major fields of research are kinematics, dynamics, and trajectory planning for kinematically redundant serial robots as well as real-time methods for solving parametricnon-linear programming problems.

This master’s thesis presents a novel approach to finding trajectories with minimal end time for kinematically redundant manipulators. Emphasis is given to a general applicability of the developed method to industrial tasks such as gluing or welding. Minimum-time trajectories may yield economic advantages as a shorter trajectory duration results in a lower task cycle time. Whereas kinematically redundant manipulators possess increased dexterity, compared to conventional non-redundant manipulators, their inverse kinematics is not unique and requires further treatment. In this work a joint space decomposition approach is introduced that takes advantage of the closed form inverse kinematics solution of non-redundant robots. Kinematic redundancy can be fully exploited to achieve minimum-time trajectories for prescribed end-effector paths.