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ГИБРИДНЫЙ МЕТОД ПЛАНИРОВАНИЯ КОНФИГУРАЦИИ МАРШРУТА НА КАРТЕ МЕСТНОСТИ В УСЛОВИЯХ ЧАСТИЧНОЙ НЕОПРЕДЕЛЕННОСТИ
This paper describes a hybrid situational trajectory planning algorithm for 2D space operating under conditions of partial uncertainty. Based on the integration of wave-propagation and ant colony optimization algorithms, it enables the real-time generation of minimum-length trajectories while simultaneously optimizing other path quality criteria. The processes of generating a trajectory segment and moving the object along it alternate at each step. Trajectory generation proceeds sequentially (step-by-step) across two hierarchical levels. The formation and orientation of the local visibility zone—and the corresponding region on the terrain map—are determined relative to the current reference vector. First-level procedures generate a chain of pairwise adjacent regions containing localized obstacles across the terrain map, step by step. Second-level procedures generate a set of possible paths for the mobile object to traverse the current region. The union of these regions forms the terrain area through which the trajectory is plotted. The complete trajectory consists of a sequence of individual paths traversing these regions, connecting the object's starting position to its target position. The solution is found by a population of agents operating on a search graph. Graph vertices correspond to grid cells within the area; an edge connects two vertices if the corresponding cells in the discrete terrain model are adjacent and a transition between them is possible. Synthesizing a trajectory and navigating a mobile object under uncertainty is a complex task requiring the integration of diverse sensor systems, data processing algorithms, path planning algorithms, and motion control systems. Continuous technological advancements in artificial intelligence, computer vision, and robotics are enabling the creation of increasingly sophisticated autonomous navigation systems. However, achieving full autonomy and guaranteed safety for a mobile object under all conditions remains a challenging area of research.