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Research on multi-UAV autonomous obstacle avoidance algorithm integrating improved dynamic window approach and ORCA.

Xucheng Chang1, Jingyu Wang2, Kang Li3

  • 1School of Automation, Zhengzhou University of Aeronautics, Zhengzhou, 450046, China.

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Summary
This summary is machine-generated.

This study introduces an improved Dynamic Window Approach (DWA) fusion algorithm for efficient UAV obstacle avoidance in complex environments. The enhanced algorithm significantly reduces flight path length, mission time, and iterations for multi-UAV systems.

Keywords:
Autonomous obstacle avoidanceImproved DWA algorithmORCA algorithmUAVs

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Area of Science:

  • Robotics and Autonomous Systems
  • Artificial Intelligence
  • Control Theory

Background:

  • Traditional Dynamic Window Approach (DWA) algorithms exhibit low efficiency in unknown and complex environments.
  • Existing DWA methods often lack a global perspective and struggle to balance computational speed with accuracy.
  • Poor environmental adaptability and limited inter-UAV obstacle-avoidance capabilities hinder the performance of conventional algorithms.

Purpose of the Study:

  • To develop an improved DWA fusion algorithm for enhanced UAV obstacle avoidance in complex, unknown environments.
  • To address the limitations of traditional DWA, including its lack of global perspective, computational efficiency challenges, and poor environmental adaptability.
  • To integrate the improved DWA with Optimal Reciprocal Collision Avoidance (ORCA) for effective multi-UAV collaborative obstacle avoidance.

Main Methods:

  • Introduced a bidirectional search strategy to enhance the global perspective of the planned trajectory.
  • Designed a dynamic time step adjustment mechanism to balance computational efficiency and accuracy.
  • Developed a trajectory evaluation function with variable weights to improve environmental adaptability.
  • Integrated the improved DWA algorithm with the Optimal Reciprocal Collision Avoidance (ORCA) method for multi-UAV collaboration.

Main Results:

  • Achieved a 27.90% reduction in UAV flight path length compared to the conventional DWA algorithm.
  • Demonstrated a 17.01% decrease in mission completion time.
  • Showcased a 21.5% reduction in iteration counts, indicating improved computational efficiency.
  • Simulation experiments validated the effectiveness of the proposed improved fusion algorithm.

Conclusions:

  • The improved DWA fusion algorithm offers superior performance in UAV obstacle avoidance within complex and unknown environments.
  • The integration with ORCA enhances multi-UAV collaborative obstacle-avoidance capabilities.
  • The algorithm presents significant practical value for engineering applications in autonomous multi-UAV systems.