PATH PLANNING ALGORITHMS IN 2D/3D SPACES USING MOBILE DEVICES FOR ENSURING COMMUNICATIONS IN CONDITIONS OF DESTRUCTION

Abstract

The article focuses on the comparative analysis of routing algorithms in 2D and 3D spaces using robotic mobile devices. The algorithms are thoroughly examined from the perspective of their use for deploying chains of drones in conditions of destruction and radio interference, which often occur during disasters and other emergency situations. Particular attention is given to identifying the rational algorithms considering a set of metrics for ensuring reliable communications and efficient execution of search-and-rescue operations.

Based on a detailed analysis of route formation algorithms in 2D/3D space in the presence of obstacles according to defined qualitative characteristics, the following conclusions can be drawn regarding their application for route finding for mobile systems.

1. For 2D space, the following algorithms are best:

- Algorithm A* (A-star): due to its ability to optimize pathfinding taking into account cost and heuristic evaluations, it shows high efficiency in 2D navigation;

- Dijkstra's algorithm: best suited for cases where you need to find the shortest path on large graphs with small weights;

- Advanced Wavefront algorithm: the ability to propagate waves from a starting point and label cells makes it ideal for scalable 2D environments.

1. In 3D space, the choice of algorithms is more limited:

- RRT (Rapidly-exploring Random Tree) algorithm: effectively solves the task of rapid random search and adaptation in complex 3D environments;

- Probabilistic Roadmap Method: the approach to the selection of nodes determines the ability to efficiently process large 3D spaces;

- Algorithm A*: versatility and ability to adapt to 3D tasks make it one of the best choices.

1. Combining different algorithms can improve routing efficiency. Examples of appropriate successful combinations of algorithms:

- A* and RRT: The combination of these algorithms can help in solving problems where it is necessary to quickly adapt to changes in the environment while providing the optimal path;

- Dijkstra and PRM: this combination can be useful for detailed work in complex environments where a combination of general planning and local detailed search is needed.

1. The analysis shows that there is a significant potential for the application and combination of different routing algorithms in solving different routing tasks in robotic systems. Effective use of algorithms depends on task conditions, environment dynamics, and computing resource requirements. The results of this research can serve as a basis for further developments in the field of robotic navigation systems, providing greater flexibility and efficiency in solving various practical tasks.
2. The novelty of the research results lies in the determination of characteristics and recommendations for the use of existing routing algorithms to create reliable communications using mobile technologies and robotic systems. Their practical significance lies in the fact that a systematized set of algorithms and provided recommendations can be used to create an information technology and decision support system for route formation.
3. Further research can be directed to the development of algorithms for decision support systems for planning [7], deployment [45] and maintenance of reliable operation [46] of flying networks, as well as combined robotic systems that combine UAVs and ground robots in conditions of moving 2D/3D obstacles, changes in conditions of use, etc.