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Path planning for volumetric flask grasping based on visual guidance and multi-constraint optimization.

Zhaopeng Yuan1, Meng Li1, Chengyun Wang1

  • 1School of Electrical Engineering, University of Jinan, Jinan, China.

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This study introduces a Vision-guided Multi-constraint RRT* (VM-RRT*) algorithm for robotic arm path planning in chemical labs. The new method enhances efficiency and precision in grasping operations, outperforming traditional algorithms.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Chemical Engineering

Background:

  • Robotic arms are crucial for automated chemical laboratory operations, particularly for tasks like grasping volumetric flasks.
  • Traditional path planning algorithms, such as Rapidly-exploring Random Tree Star (RRT*), face challenges with low sampling efficiency and jerky movements.

Purpose of the Study:

  • To develop an improved path planning algorithm for robotic arms in automated chemical laboratories.
  • To enhance the efficiency, precision, and smoothness of grasping operations for volumetric flasks.

Main Methods:

  • Proposed the Vision-guided Multi-constraint RRT* (VM-RRT*) algorithm, integrating visual guidance and multi-constraint path planning.
  • Utilized target detection for spatial coordinate determination of volumetric flasks to reduce exploration.
  • Employed cubic B-splines for path fitting, spline interpolation for data point density, and low-pass filtering for trajectory optimization.

Main Results:

  • The VM-RRT* algorithm demonstrated an average planning time of 3.27 seconds, approximately 20% faster than the traditional RRT* algorithm (4.07 seconds).
  • Achieved effective control over robotic arm end-effector motion parameters, reducing speed and acceleration fluctuations.
  • Successfully optimized multi-constraint trajectories for smoother and more precise robotic arm movements.

Conclusions:

  • The VM-RRT* algorithm significantly improves experimental efficiency in automated chemical laboratories.
  • The developed algorithm provides robust support for laboratory automation by ensuring precise and efficient robotic arm operations.