For the high-precision positioning requirements of UAV formation cooperative operation, a distributed control system based on RTK technology is proposed in this paper. By using the U-blox F9P GNSS module to build an RTK base station/mobile terminal, combined with Pixhawk 6C flight control and MAVESP8266 communication module, centimeter-level (< 2 cm) positioning accuracy is achieved. The system adopts the “centralized planning distributed execution” architecture, transmits RTCM differential data and MAVLink messages through the UDP protocol, and integrates ROS to realize status information subscription. Experiments show that the system can effectively support large area surveying and mapping and other complex tasks, and significantly improve the autonomy and reliability of formation operations.
Wilson H, 2019, Optimization Techniques for Single-Rotor UAV Systems: Power, Stability and Navigation, thesis, ETH Zurich Research Collection, Swiss Federal Institute of Technology Zurich, 75–98.
Chen Y, 2021, Distributed Formation Control for Agricultural UAV Swarms: Spraying and Monitoring Applications, dissertation, University of Michigan Deep Blue, University of Michigan, 112–135.
Johnson M, 2018, Early UAV Formation Systems: A Case Study of Fire Bee Target Drones, dissertation, ProQuest Dissertations Publishing, Stanford University, 33–57.
Smith R, 2020, Distributed Control Architectures for Multi-Agent UAV Systems, thesis, MIT DSpace, Massachusetts Institute of Technology, 89–112.
Wilson E, 2019, Contract Network Protocols in UAV Swarm Coordination, dissertation, Harvard University Archives, Harvard University, 145–168.
Chen L, 2021, From RoboFlag to Modern UAV Swarms: Evolution of Distributed SLAM, thesis, CaltechTHESIS, California Institute of Technology, 72–95.
Brown K, 2022, Adaptive Formation Algorithms in Autonomous UAV Systems, dissertation, University of Michigan Deep Blue, University of Michigan, 118–142.
Davis P, 2023, Convergence of Aviation Engineering and Distributed AI in UAV Development, thesis, ETH Zurich Research Collection, Swiss Federal Institute of Technology Zurich, 55–78.
Chen L, 2023, Deep Reinforcement Learning for Autonomous UAV Navigation. Science Robotics, 8(75): eabf3190.
Park S, 2024, 5G-Enabled Collaborative Control of Multi-Rotor UAVs. IEEE Internet of Things Journal, 11(5): 4321–4335.
Anderson B, 2022, GPS Limitations in UAV Swarm Navigation: Ionospheric Effects and Urban Challenges, dissertation, MIT DSpace, Massachusetts Institute of Technology, 45–68.
Zhang K, 2023, RTK-Enhanced Distributed Control for Centimeter-Accurate UAV Formation Flight, thesis, ETH Zurich Research Collection, Swiss Federal Institute of Technology Zurich, 112–135.