Time-optimal Trajectory Planning For Redundant Robots: Joint Space Decomposition For Redundancy Resolution In Non-linear Optimization (bestmasters)
by Alexander Reiter /
2016 / English / PDF
1.9 MB Download
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.
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.
