Area reconnaissance modeling of modular reconnaissance robotic systems

Abstract

In terms of deploying forces and assets in different domains, the conduct of contemporary military operations can be characterized as complex. Information obtained from a wide range of sources and sensors is thus a crucial factor influencing the course and outcome of an operation. It must be robust, variably deployable, sustainable long-term, modular, and flexible when performing reconnaissance tasks in the rear of enemy forces or in areas threatened by, for example, chemical, biological, radiological, and/or nuclear (CBRN) threats. This paper describes the requirements of commanders for the capabilities of autonomous modular robotic systems performing reconnaissance tasks to support their units. It characterizes the possibilities of using mathematical-algorithmic models in planning the operation of robotic systems. The computational capabilities of tactical decision support system models are demonstrated on two scenarios for the reconnaissance of an area of interest. The partial calculations of the different parts of the reconnaissance task are performed in a logical sequence. Field tests practically verified the variants of performing reconnaissance tasks by robotic systems. The use of digital terrain and relief models, mathematical-algorithmic models, and variant modeling has increased the efficiency of the planning and deployment of a group of robotic systems in the reconnaissance of an area of interest.