3D Trajectory Planning Method for UAVs Swarm in Building Emergencies.

Area of Science:

• Robotics and Autonomous Systems
• Artificial Intelligence
• Computer Science

Background:

• Multi-Robot Systems (MRS) offer robustness and versatility for autonomous tasks.
• Cooperative Unmanned Aerial Vehicle (UAV) operations require sophisticated trajectory planning for safe, collision-free movement.
• Emergency response in urban environments necessitates efficient autonomous systems.

Purpose of the Study:

• To develop and validate a multi-trajectory planning method for UAV swarms using 3D Probabilistic Roadmaps (PRM).
• To support Emergency Response Teams (ERT) in urban emergencies with autonomous UAV capabilities.
• To present a Robot Operating System (ROS)-based architecture for simulating and integrating the developed methods.

Main Methods:

• Utilized 3D Probabilistic Roadmaps (PRM) for multi-trajectory planning in a UAV swarm.
• Developed a ROS-based architecture enabling MavLink communication and Pixhawk autopilot integration.
• Simulated building emergencies to validate the proposed method's effectiveness.

Main Results:

• The PRM-based approach demonstrated effective solutions with efficient calculation times for scalable UAV systems.
• The ROS architecture facilitated seamless integration and simulation for real-world UAV swarm deployment.
• Successful validation through simulated emergency scenarios confirmed the system's viability.

Conclusions:

• PRM-based trajectory planning is an effective strategy for scalable multi-UAV systems, particularly in dynamic environments like urban emergencies.
• The integrated ROS framework provides a versatile platform for developing and deploying autonomous UAV swarms.
• The developed system offers a practical solution for enhancing emergency response capabilities through autonomous robotics.