Routing of Autonomous Devices in Three-Dimensional Space

The article addresses the problem of routing autonomous devices in three-dimensional space, which is a relevant task for intelligent control. The three-dimensional space is characterized by a high degree of freedom, complex topology, and dynamic environmental changes, which significantly complicate the task of effective trajectory planning. The development of routing methods that ensure safety, energy efficiency, and computational efficiency is crucial for improving the performance of autonomous systems. The paper presents a comprehensive routing system based on a hybrid approach that combines high-level modeling of the working space with metaheuristic optimization methods. Hierarchical data structures, such as octrees, are used to represent the three-dimensional environment, providing compactness and flexibility for spatial models. These models are transformed into graph structures, allowing the routing problem to be described as an optimization problem on graphs. A modified metaheuristic ant colony optimization algorithm, belonging to the class of swarm optimization methods, is proposed. The algorithm is designed to build safe and energy-efficient routes, as well as to solve problems related to finding the shortest Hamiltonian cycles and dynamically reconfiguring routes in a changing external environment. The paper presents the results of computational experiments, including algorithm testing in three-dimensional space and a comparative analysis with other routing algorithms. The computational experiment confirmed the effectiveness of the developed routing algorithm, including reduced computation time and improved energy efficiency of autonomous devices. The prospects for further research include integrating the proposed system into a wide range of applications for autonomous devices aimed at optimizing control processes and enhancing performance in a dynamically changing external environment. It is worth noting that the developed algorithm can be adapted to solve complex tasks where routing and wind generator placement on a plane are interrelated. The placement problem is directly connected to route construction for servicing these objects, which requires a comprehensive approach for an efficient solution. This will be part of a decision support system designed for the planning and servicing of wind power complexes, ensuring their effective operation and resource management.

metaheuristic algorithm, ant colony optimization, graph-based mathematical models, routing, three-dimensional space modeling, energy systems