Optimal path selection algorithm for UAV formation guided by a UV virtual fence.

Area of Science:

• Robotics and Autonomous Systems
• Wireless Communication Networks
• Optimization Algorithms

Background:

• Unmanned Aerial Vehicle (UAV) formations require efficient path planning in complex environments.
• Wireless Ultraviolet (UV) light communication offers unique properties for network coverage.
• Existing algorithms may not optimally handle obstacle avoidance for UAV formations.

Purpose of the Study:

• To develop an optimal flight path selection strategy for UAV formations in areas with multiple obstacles.
• To propose a novel wireless UV light self-organizing network coverage model.
• To enhance obstacle avoidance capabilities and efficiency of UAV formations.

Main Methods:

• A wireless UV light self-organizing network coverage model is proposed, categorizing UV light by wavelength into detection, communication, and early warning areas.
• A consensus algorithm with leaders and followers is designed for UAV formation control.
• The artificial potential field method is integrated to ensure effective obstacle avoidance.

Main Results:

• The improved algorithm enables UAV formations to select reasonable flight routes in multi-obstacle environments.
• Average obstacle avoidance time is reduced by 6.75 seconds compared to the original algorithm.
• UAV obstacle avoidance range in multi-obstacle environments is limited to approximately 1 meter.

Conclusions:

• The proposed UV light self-organizing coverage model and improved algorithm enhance UAV formation navigation and obstacle avoidance.
• The developed methods are suitable for applications in military communications and disaster relief operations.
• This research contributes to safer and more efficient UAV operations in challenging terrains.