Abstract Autonomous mobile robotics needs reliable information on relief of underlying surface and location of obstacles. Planning the route of a mobile on-ground robot supposes mapping of a visible area with separating it into zones of good or conditional pass ability, impassability, and indefinite zones. It needs recognition of standard objects (marking, traffic signs) and types of surface (snow, sand, or water) as sources of evident or hidden obstacles. 3D calculation requires large computer resources and leads to delays, limiting the velocity. Contouring of boundaries simplifies image decomposition to objects and defines key tasks of mapping such as image vectorization and recognition of objects. They must be divided as in algorithms so at a hardware level. An idea of process multisequencing results in division of data processing on several processors. Along with vector analysis of obstacles it leads to radical cut of 3D update time, ensuring the data supply for high-speed motion of robots.
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