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An Improved Global and Local Fusion Path-Planning Algorithm for Mobile Robots.

Yongliang Shi1, Shucheng Huang1, Mingxing Li2

  • 1School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang 212100, China.

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Summary
This summary is machine-generated.

This study introduces a new path-planning algorithm for mobile robots, improving efficiency and adaptability. The novel approach reduces path redundancy and turning points in complex environments.

Keywords:
fusion path-planning algorithmglobal path-planning algorithmlocal path-planning algorithmmobile robot

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Area of Science:

  • Robotics
  • Artificial Intelligence

Background:

  • Path planning is crucial for mobile robot navigation.
  • Current methods exhibit path redundancy, excessive turns, and poor environmental adaptability.

Purpose of the Study:

  • To propose a novel global and local fusion path-planning algorithm.
  • To enhance robot adaptability and reduce path inefficiencies in complex scenarios.

Main Methods:

  • Developed a new heuristic function and improved path generation for global planning.
  • Implemented an environment-aware dynamic parameter adjustment for local planning, including obstacle evaluation.
  • Fused global and local planning strategies into a cohesive algorithm.

Main Results:

  • Reduced path redundancy and excessive turning points.
  • Improved adaptability to complex environments.
  • Demonstrated higher operational efficiency through simulations.

Conclusions:

  • The fusion path-planning algorithm effectively addresses limitations of existing methods.
  • The proposed algorithm enhances mobile robot performance in challenging environments.
  • Achieved significant improvements in path efficiency and obstacle avoidance.