The paper describes a hybrid algorithm for situational trajectory planning under partial uncertainty for a two-dimensional space based on the integration of the wave and ant algorithms, which allows constructing trajectories of minimum length in real time with simultaneous optimization of a number of other quality criteria for the constructed path. The processes of forming a trajectory section and moving an object along it alternate at each step. The trajectory is formed sequentially (step by step) at two levels of each step. The local visibility zone and the region covered by it on the terrain map are formed and oriented relative to the current reference vector. The first-level procedures sequentially form a chain of pairwise adjacent regions with localized obstacles on the terrain map in steps. The second-level procedures form a set of trajectories for the passage of a moving object through a region at a step. When the chain of regions merges, a terrain region is formed through which the trajectory is laid. The entire trajectory is a set of individual trajectories for the passage of a moving object through regions connecting its initial position with the target position. The search for a solution is carried out by a population of agents on a solution search graph. The vertices of the set correspond to the cells of the region. Two vertices are connected by an edge if the corresponding cells on the terrain model in the form of a discrete working field are adjacent and the transition of the connection from one cell to another is possible. It should be noted that the synthesis of the trajectory and the movement of a moving object under uncertainty is a complex task that requires the integration of various sensor systems, data processing algorithms, path planning algorithms and motion control systems. The constant development of technologies in the fields of artificial intelligence, machine vision and robotics allows the creation of increasingly sophisticated autonomous navigation systems. However, complete autonomy and guaranteed safety of a moving object under any conditions still remain complex tasks for research.
