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The EBS-A* algorithm: An improved A* algorithm for path planning.

Huanwei Wang1, Shangjie Lou1, Jing Jing1

  • 1State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, China.

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|February 17, 2022
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Summary
This summary is machine-generated.

This study introduces the EBS-A* algorithm, enhancing mobile robot path planning by incorporating expansion distance, bidirectional search, and smoothing. This improved A* algorithm significantly boosts planning efficiency and safety near obstacles.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Science

Background:

  • Path planning is crucial for mobile robot navigation.
  • The traditional A* algorithm, while effective, suffers from slow planning speeds and proximity to obstacles.

Purpose of the Study:

  • To propose an improved A*-based algorithm, EBS-A*, for enhanced mobile robot path planning.
  • To address limitations of the traditional A* algorithm, including speed and safety near obstacles.

Main Methods:

  • Introduced expansion distance for obstacle avoidance.
  • Implemented bidirectional search for simultaneous start and goal node exploration.
  • Incorporated smoothing to reduce sharp turns and improve path robustness.

Main Results:

  • The EBS-A* algorithm demonstrated a 278% improvement in path planning efficiency.
  • Reduced critical nodes by 91.89% and eliminated right-angle turns (100% reduction).
  • Effectiveness verified through simulations and transfer to a Robot Operating System (ROS).

Conclusions:

  • The EBS-A* algorithm offers a significant advancement over the traditional A* algorithm for mobile robot path planning.
  • The enhancements lead to faster, safer, and more robust navigation.