Alexander Reiter • Time-Optimal Trajectory Planning for Redundant Robots

Alexander Reiter • Time-Optimal Trajectory Planning for Redundant Robots

Joint Space Decomposition for Redundancy Resolution in Non-Linear Optimization
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.

Contents

• NURBS Curves
• Modeling: Kinematics and Dynamics of Redundant Robots
• Approaches to Minimum-Time Trajectory Planning
• Joint Space Decomposition Approach
• Examples for Applications of Robots

Target Groups

• Lecturers and Students of Robotics and Automation
• Industrial Developers of Trajectory Planning Algorithms