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An improved beetle antennae search path planning algorithm for vehicles.

Qing Liang1, Huike Zhou1, Yafang Yin1

  • 1Xi'an University of Posts and Telecommunications, School of Electronic Engineering, Xi'an, Shaanxi Province, China.

Plos One
|September 15, 2022
PubMed
Summary
This summary is machine-generated.

This study enhances mobile robot path planning by improving the Beetle Antennae Search (BAS) algorithm. The new method offers more reliable and robust navigation in unknown environments, overcoming local optimum issues.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Science

Background:

  • Mobile robot path planning is crucial for autonomous navigation in unknown environments.
  • Traditional algorithms like Beetle Antennae Search (BAS) suffer from local optima and low optimization accuracy.

Purpose of the Study:

  • To propose an improved Beetle Antennae Search (BAS) algorithm for mobile robot local path planning.
  • To enhance path reliability, robustness, and avoid local optima in unknown environments.

Main Methods:

  • Introduced a map safety threshold to ensure clearance from obstacles.
  • Incorporated virtual target points to mitigate local optima.
  • Applied B-spline smoothing to enhance path robustness and reduce sharp turns.

Main Results:

  • The improved BAS algorithm demonstrated superior performance in path planning simulations.
  • Effectiveness was verified through comparisons with existing path planning algorithms.
  • The enhancements successfully addressed issues of local optima and low accuracy.

Conclusions:

  • The proposed enhanced BAS algorithm offers a more reliable and robust solution for mobile robot path planning.
  • This method is effective in navigating unknown environments, overcoming limitations of traditional approaches.