Formation flight and collision avoidance for multiple UAVs based on modified tentacle algorithm in unstructured...

Area of Science:

• Robotics
• Aerospace Engineering
• Artificial Intelligence

Background:

• Unmanned aerial vehicles (UAVs) face challenges in high-speed formation flight and collision avoidance, especially in unstructured environments.
• Existing tentacle algorithms struggle with computational demands and adaptability for multi-UAV systems.

Purpose of the Study:

• To develop an efficient and robust method for formation flight and collision avoidance in multiple UAVs.
• To address the limitations of conventional tentacle algorithms in terms of speed and computational complexity.

Main Methods:

• A modified tentacle algorithm is proposed, featuring rapid matching of tentacle radius and steering commands to solve data calculation issues.
• Speed sets and tentacles are reduced and reconstructed for multi-UAV application.
• The best tentacle is selected for rapid UAV collision avoidance path generation, avoiding iterative optimization.

Main Results:

• The modified tentacle algorithm demonstrates high performance in collision avoidance for multiple UAVs.
• Simulation results confirm effective enhancement of formation flight and collision avoidance capabilities.
• The method proves efficient in unstructured environments and for high-speed UAVs.

Conclusions:

• The proposed modified tentacle algorithm significantly improves the performance of multi-UAV formation flight and collision avoidance.
• This approach offers a computationally efficient solution for complex, dynamic environments.
• The study validates the effectiveness of the modified algorithm for real-world UAV applications.