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Fast Path Planning for Kinematic Smoothing of Robotic Manipulator Motion.

Hui Liu1, Yunfan Li1, Zhaofeng Yang1

  • 1School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China.

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Summary

This study introduces a new algorithm, KSBB-P-RRT*, for robotic path planning that integrates motion control to prevent shocks and vibrations. The enhanced algorithm improves efficiency and reduces path cost, making it suitable for precision robotics.

Keywords:
RRT*artificial potential fieldpath plannings-curve acceleration/deceleration

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Area of Science:

  • Robotics
  • Control Engineering
  • Artificial Intelligence

Background:

  • The Rapidly-exploring Random Tree Star (RRT*) algorithm is a common choice for robotic manipulator path planning.
  • However, RRT* does not inherently address motion control, leading to potential issues like shocks and vibrations that reduce accuracy and stability.

Purpose of the Study:

  • To propose a novel algorithm, Kinematically Smoothed, dynamically Biased Bidirectional Potential-guided RRT* (KSBB-P-RRT*), that unifies path planning and motion control.
  • To enhance the efficiency and stability of robotic path planning by addressing limitations in existing RRT* algorithms.

Main Methods:

  • Developed the KSBB-P-RRT* algorithm with three key innovations: a fast path search strategy using Bi-RRT* with adaptive sampling and steering, triangle-inequality-based optimization for waypoint reduction, and a kinematically constrained smoothing strategy using a Jerk-Continuous S-Curve.
  • Integrated path planning with motion control to ensure smooth and executable trajectories.

Main Results:

  • Simulations demonstrated that KSBB-P-RRT* reduced planning time by at least 30% and path cost by at least 3% compared to Bi-RRT*.
  • The algorithm required fewer iterations, indicating improved efficiency and effectiveness.

Conclusions:

  • The KSBB-P-RRT* algorithm successfully integrates path planning and motion control, offering smoother and more stable trajectories.
  • Its proven effectiveness and suitability for complex, precision-demanding applications, such as agricultural robotics, highlight its practical value.