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Time-Impact Optimal Trajectory Planning for Wafer-Handling Robotic Arms Based on the Improved Snake Optimization

Yujie Ji1, Jiale Yu1

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

Sensors (Basel, Switzerland)
|April 28, 2025
PubMed
Summary

This study introduces an Improved Snake Optimization (ISO) algorithm for robotic arm trajectory planning, significantly reducing motion impact and vibration. The ISO algorithm enhances efficiency by 24.1% and improves optimization performance by over 60%.

Keywords:
ISO algorithmS-shaped speed curvetime-impact optimaltrajectory planning

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Optimization Algorithms

Background:

  • Wafer-handling robotic arms require efficient and smooth motion to prevent damage and improve productivity.
  • Existing trajectory planning methods often struggle to minimize impact and vibration simultaneously.
  • Optimization algorithms need refinement for complex, real-world robotic applications.

Purpose of the Study:

  • To develop an improved trajectory planning approach for wafer-handling robotic arms.
  • To reduce impact and vibration during robotic arm motion.
  • To enhance the working efficiency of robotic systems through advanced optimization.

Main Methods:

  • An Improved Snake Optimization (ISO) algorithm was developed, incorporating Chaotic Tent Map initialization, dynamic learning factors, cosine annealing learning rate, and Bayesian optimization.
  • The ISO algorithm was applied to trajectory planning in the Cartesian space for robotic arms.
  • The planning focused on single-segment start-stop S-shaped speed curves with arc transitions.

Main Results:

  • The ISO algorithm achieved a 24.1% increase in the improved S-shaped speed curve compared to the original plan.
  • Mean and variance rankings of the ISO algorithm showed significant improvements of 60.8% and 63.4%, respectively, over the standard Snake Optimization (SO) algorithm.
  • A Pareto optimal solution minimizing time and impact was successfully obtained using MATLAB simulations.

Conclusions:

  • The proposed Improved Snake Optimization algorithm effectively enhances robotic arm trajectory planning.
  • ISO significantly reduces motion impact and vibration while improving working efficiency.
  • This approach offers a robust method for achieving optimal performance in robotic motion control.