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A Consistent Round-Up Strategy Based on PPO Path Optimization for the Leader-Follower Tracking Problem.

Xiao Wang1, Zhaohui Yang1, Xueqian Bai1

  • 1College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.

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|November 14, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a cooperative multi-unmanned aerial vehicle (UAV) strategy for target tracking and obstacle avoidance. The novel approach ensures high mission success rates, even without initial target detection.

Keywords:
UAV formation controlconsistency protocolreinforcement learning

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Area of Science:

  • Robotics and Control Systems
  • Artificial Intelligence and Machine Learning
  • Aerospace Engineering

Background:

  • Single unmanned aerial vehicles (UAVs) possess limitations in complex missions, impacting mission success and survivability.
  • Traditional control methods for multi-UAV systems struggle with adaptability in unstable environments and require extensive environmental data.
  • Cooperative multi-UAV formations offer enhanced capabilities but face challenges with scalability and dynamic conditions.

Purpose of the Study:

  • To develop a robust and adaptive control strategy for multi-UAV systems to overcome limitations of single UAVs and traditional methods.
  • To enhance mission success rates and survivability of UAVs through cooperative formation control.
  • To enable effective target tracking and obstacle avoidance in dynamic environments without prior target detection.

Main Methods:

  • Proposed a consistent round-up strategy utilizing Proximal Policy Optimization (PPO) for path optimization and target tracking.
  • Trained a leader UAV using PPO for autonomous obstacle avoidance and target tracking.
  • Developed a communication network for follower UAVs to receive environmental information from the leader, enabling a tracking control law based on consistency protocols and the Apollonian circle.

Main Results:

  • The proposed strategy successfully achieved target UAV round-up and obstacle avoidance for the pursuing multi-UAV group.
  • The system demonstrated effectiveness even without initial target detection.
  • Simulated scenarios showed a consistent success rate above 80% for the multi-UAV cluster in rounding up targets.

Conclusions:

  • The PPO-based consistent round-up strategy significantly improves the performance and adaptability of multi-UAV systems.
  • Cooperative control and communication networks are crucial for enhancing UAV capabilities in complex, dynamic environments.
  • The developed method offers a promising solution for autonomous target pursuit and navigation in challenging scenarios.