Content area
Unmanned Aerial Vehicles (UAVs) are aircraft systems that operate remotely or autonomously using on-board computers without the need for a human pilot. This paper investigates the split control design of UAV swarms utilizing the master–slave paradigm, which improves UAV operations in complicated situations, including search and rescue missions, border monitoring, and disaster response. The proposed system ensures strong communication and steady flight formations by combining genetic algorithms with A* algorithms for effective trajectory planning. We specifically designed a new ZigBee-based communications protocol to address the unique challenges associated with UAV communications within FANETs (flying ad hoc networks). We cover the decentralized architecture of the FANET framework. Finally, we test the efficiency of our protocol by integrating a Raspberry Pi 3 Model B board with the XBEE PRO S3B 915 MHz module into a DJI Phantom 3 Standard UAV. Findings showed that the UAV and ground station successfully transmitted images across different test conditions while maintaining consistent performance levels.
Article Highlights
The work uses stable formations and decentralized control to improve UAV swarm efficiency in difficult missions.
In UAV networks, a ZigBee-based communication protocol guarantees reliable data sharing under a variety of circumstances.
Optimized route planning with hybrid algorithms enhances obstacle navigation, energy efficiency, and UAV flight stability.
Details
Decentralized control;
Collaboration;
Telemetry;
Disaster recovery;
Algorithms;
Communication;
Evacuations & rescues;
Energy efficiency;
Disaster management;
Unmanned aerial vehicles;
Airborne/spaceborne computers;
Flight;
Search and rescue;
Energy consumption;
Data compression;
Search and rescue missions;
Data integrity;
Control algorithms;
Genetic algorithms;
Infrastructure;
Aircraft stability;
Route planning;
Sensors;
Ad hoc networks;
Communications networks;
Image transmission;
Communications systems;
Onboard equipment;
Connectivity;
Drones;
Computers;
Trajectory planning;
Obstacle avoidance;
Aircraft control;
Ground stations