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A path planning method using modified harris hawks optimization algorithm for mobile robots.

Cuicui Cai1, Chaochuan Jia1, Yao Nie1

  • 1College of Electronics and Information Engineering, West Anhui University, Lu'an, China.

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|August 7, 2023
PubMed
Summary
This summary is machine-generated.

A new modified Harris Hawks Optimization (MHHO) algorithm enhances mobile robot path planning by avoiding local optima and shortening path distances. This improved algorithm offers faster convergence and better path quality compared to existing methods.

Keywords:
Harris hawks optimization algorithmMobile robotObstacle avoidanceOptimal pathPath planning

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Optimization Algorithms

Background:

  • Path planning is crucial for mobile robot efficiency.
  • Conventional algorithms often struggle with local optima in complex environments.
  • Improving path quality and convergence speed remains a key challenge.

Purpose of the Study:

  • To propose a modified Harris Hawks Optimization (MHHO) algorithm for mobile robot path planning.
  • To enhance path quality, smoothness, and reduce path distance.
  • To overcome the limitations of local optima and improve convergence speed.

Main Methods:

  • Implementing a modified Harris Hawks Optimization (MHHO) algorithm.
  • Incorporating a linear path strategy to straighten path segments.
  • Applying a local search update strategy to escape local optima.
  • Utilizing a nonlinear control strategy for improved convergence.

Main Results:

  • The MHHO algorithm demonstrated superior performance in path length and convergence speed.
  • Experimental results showed MHHO outperforming Ant Colony Optimization (ACO), Improved Sparrow Search Algorithm (ISSA), and standard HHO.
  • The proposed method effectively generated smoother and shorter paths.

Conclusions:

  • The MHHO algorithm provides an effective solution for mobile robot path planning in complex environments.
  • MHHO offers significant improvements in efficiency, path quality, and convergence over existing algorithms.
  • This research contributes to advancing autonomous robot navigation capabilities.