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Wafer Handing Robotic Arm Vibration Trajectory Planning Based on Graylag Goose Optimization.

Yujie Ji1, Peiyan Hu1

  • 1School of Mechanical Engineering, Shenyang Ligong University, Shenyang 110159, China.

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Semiconductor wafer-handling robots use Gray Goose Optimization (GGO) to suppress vibrations. This method improves positioning accuracy and system stability by optimizing trajectories for faster, smoother wafer transport.

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Area of Science:

  • Robotics and Automation
  • Control Systems Engineering
  • Optimization Algorithms

Background:

  • Wafer-handling robots are critical in semiconductor manufacturing for high-speed, precise transport.
  • Flexible components in lightweight, rapid-motion robots cause residual vibrations, reducing accuracy and stability.

Purpose of the Study:

  • To propose a novel vibration-suppression trajectory planning method for wafer-handling robots.
  • To enhance positioning accuracy and system stability in semiconductor manufacturing.

Main Methods:

  • Utilized the Gray Goose Optimization (GGO) algorithm for multi-objective trajectory planning.
  • Developed a multi-objective function balancing motion time and vibration energy.
  • Determined optimal switching time points for S-shaped velocity profiles.

Main Results:

  • GGO algorithm demonstrated effectiveness and robustness on benchmark functions.
  • Planned trajectories showed negligible displacement variation under disturbances.
  • Achieved Pareto-optimal solutions balancing motion time and residual vibration energy.

Conclusions:

  • The GGO-based method effectively suppresses vibrations in wafer-handling robots.
  • The approach enhances trajectory smoothness, velocity, and acceleration control.
  • This leads to improved positioning accuracy and system stability in semiconductor manufacturing.