Time-Optimal Trajectory Planning for Redundant Robots: Joint Space Decomposition for Redundancy Resolution in Non-Linear Optimi

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Time-Optimal Trajectory Planning for Redundant Robots: Joint Space Decomposition for Redundancy Resolution in Non-Linear Optimi

Alexander Reiter, "Time-Optimal Trajectory Planning for Redundant Robots: Joint Space Decomposition for Redundancy Resolution in Non-Linear Optimization"
2016 | ISBN-10: 3658127007 | 108 pages | PDF | 2 MB


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.
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Tags: Optimal, Trajectory, Planning, Redundant, Robots, Decomposition, Redundancy, Resolution, Linear, Optimi

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