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A Novel Cost Calculation Method for Manipulator Trajectory Planning.

Leiyang Fu1,2, Shaowen Li1,2

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Calculating manipulator execution cost is crucial for agricultural robots. This study introduces a novel cost function using mass, iteration, and residual, outperforming existing trajectory planning methods.

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Area of Science:

  • Robotics
  • Control Systems
  • Artificial Intelligence

Background:

  • Trajectory planning for manipulators is essential for robotic applications, particularly in agriculture.
  • Existing methods often optimize for single factors like time or distance, neglecting a holistic approach.
  • The Denavit-Hartenberg (D-H) method is a traditional approach for manipulator kinematics.

Purpose of the Study:

  • To develop and validate a comprehensive cost function for assessing manipulator effort in trajectory planning.
  • To compare the proposed cost function against state-of-the-art methods like Double A* and MoveIt.
  • To evaluate the feasibility of using the Robotics Toolbox for manipulator trajectory planning in agricultural robots.

Main Methods:

  • Utilized the Python version of the Robotics Toolbox for manipulator trajectory planning.
  • Developed a novel cost function incorporating mass, iteration, and residual.
  • Implemented and compared three inverse kinematics methods: Newton-Raphson (NR), Gauss-Newton (GN), and Levenberg-Marquardt (LM).

Main Results:

  • The proposed cost function demonstrated feasibility and effectiveness in assessing manipulator effort.
  • The developed method proved valid and stable when compared to Double A* and MoveIt.
  • Levenberg-Marquardt (LM) with Chan λ = 0.1 was successfully applied in mobile operations on an agricultural robot platform.

Conclusions:

  • The novel cost function provides a more synthetic assessment of manipulator effort for trajectory planning.
  • The Robotics Toolbox offers a viable alternative to traditional methods for manipulator trajectory planning.
  • The validated approach is suitable for real-world applications, including mobile operations in agriculture.