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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
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Adaptive Hybrid PSO-APF Algorithm for Advanced Path Planning in Next-Generation Autonomous Robots.

Abdelmadjid Benmachiche1, Makhlouf Derdour2, Moustafa Sadek Kahil2

  • 1Laboratory of Computer Science and Applied Mathematics, Chadli Bendjedid University, El-Tarf 36000, Algeria.

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|September 27, 2025
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Summary
This summary is machine-generated.

This study introduces a new path planning method for autonomous robots, combining particle swarm optimization (PSO) and artificial potential field (APF) for efficient obstacle avoidance. The approach enhances robot navigation safety and adaptability in dynamic environments.

Keywords:
APFPSOautonomous mobile robotnavigationobstacle avoidancepath planning

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Optimization Algorithms

Background:

  • Autonomous robots require sophisticated navigation systems for obstacle avoidance.
  • Dynamic environments pose significant challenges for robot path planning.

Purpose of the Study:

  • To develop an efficient and sustainable path planning approach for mobile robots.
  • To enhance robot navigation in environments with static and dynamic obstacles.

Main Methods:

  • Integration of Particle Swarm Optimization (PSO) and Artificial Potential Field (APF) algorithms.
  • Dynamic path replanning and recalculation for obstacle avoidance.
  • Continuous shortest distance calculation and robot position adjustment.

Main Results:

  • Reduced path length by 18%.
  • Achieved 90% obstacle avoidance efficiency.
  • Increased success rate by 85% in dynamic environments.
  • Demonstrated reduced computation time and improved efficiency.

Conclusions:

  • The proposed PSO-APF method offers a robust solution for autonomous robot navigation.
  • The approach ensures efficient and safe robot movement in complex and changing environments.