MODELS OF SEAMLESS OPERATION OF A GROUP OF AGRICULTURAL UAVS
Abstract
The introduction of groups of unmanned aerial vehicles (UAVs) into precision farming is hampered by several problems related to the stability of communications in areas remote from the take-off point and dependence on weather conditions, which can reduce the effectiveness of the technology. Existing planning models are insufficiently adaptive to dynamic changes in the agricultural environment, communication problems, and in most cases assume strict adherence to fixed trajectories. The purpose of this study is to develop conceptual models of seamless operation and a communication system for coordinating a group of agricultural UAVs. The paper presents a diagram of the connectivity of the system elements, which ensures the continuity of processes from initialization to automatic battery replacement and UAV refueling. A communication model of the system with the relay node has been developed that separates traffic, which makes it possible to eliminate collisions and stabilize data exchange over distances of more than 2.5 km. A method for distributing tasks, considering the energy supply and spatial coordinates of the UAV, is presented, which allows dynamically redistributing the load in case of failures. The proposed solutions enhance the autonomy and fault tolerance of the UAV group, minimize operator involvement, and ensure safe mission performance in a non-deterministic environment. The approbation of the proposed model, performed in laboratory and field conditions, showed its stability when transmitting data over extended distances and in group operation. The absence of collisions during data exchange between UAVs has been separately confirmed, which indicates the correctness of traffic separation and the effectiveness of the chosen communication architecture. The results obtained confirm the possibility of practical application of the developed models to increase the autonomy and continuity of agricultural work. The developed approach also demonstrates the potential for scaling, which expands the scope of its application in precision farming tasks.
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