Optimal Trajectory Planning of the Variable-Stiffness Flexible Manipulator Based on CADE Algorithm for Vibration...

Area of Science:

• Robotics
• Control Systems Engineering
• Applied Physics

Background:

• Robotic manipulators are crucial for precision tasks in medicine.
• Vibration suppression is vital for the stability and safety of robotic operations.
• Flexible robotic manipulators present unique challenges due to their inherent vibrations.

Purpose of the Study:

• To propose an optimal trajectory planning control method for vibration suppression in variable-stiffness flexible manipulators.
• To address the rigid-flexible coupling in manipulator dynamics.
• To enhance the stability and safety of robotic manipulators in medical applications.

Main Methods:

• Constructed a distributed dynamic physical model of the variable-stiffness flexible manipulator using Hamilton's theory.
• Designed a vibration damping controller for the flexible manipulator, considering nonlinear input.
• Employed the Cloud Adaptive Differential Evolution (CADE) optimization algorithm for trajectory planning.

Main Results:

• Compared vibration suppression effects between conventional and variable-stiffness manipulators.
• Analyzed vibration responses from different motion trajectories.
• Achieved optimal trajectory planning with minimized vibration displacement, energy consumption, and trajectory tracking deviation.

Conclusions:

• The proposed optimal trajectory planning method effectively suppresses vibrations in variable-stiffness flexible manipulators.
• The CADE algorithm validates the trajectory planning approach through numerical simulations.
• This research contributes to safer and more stable robotic operations in precision-demanding fields like medicine.