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The paper sets out the results of an experiment carried out using MASA SWORD simulator to verify the use of the unmanned aerial vehicle (UAV) reconnaissance model during battalion force protection activities. The authors focus particularly on the first phase of the battle—enemy approaching and early reconnaissance. The reconnaissance was planned using the UAV reconnaissance model which is part of the Tactical Decision Support System (TDSS). The aim of the experiment is to verify the possibilities of using the UAV reconnaissance model for battalion-size unit force protection and to compare this model with ordinarily used tactical procedures. The experiment proves the hypothesis defined in the introduction and quantifies some defined variables. Based on the result of the experiment, it is possible to state that UAV reconnaissance has significant impact on the effectiveness of the military mission. Moreover, the simulation environment opens a wide range of possibilities for future research including multiple simulations of the scenario, comparison of achieved results in dependence on the set conditions and variable settings, tailoring tactics for the scenario at hand, and so on.

The paper sets out the results of an experiment carried out using the Virtual Battle Space 2 simulator to verify the applicability of an autonomous unmanned aerial system (UAS) reconnaissance model when moving oversized loads. The model is originally implemented within a decision-support system under military conditions. The aim of the experiment is to verify the possibilities of using the model for civilian needs. The basic output of the experiment presented in the paper is confirmation that the autonomous UAS reconnaissance model can be applied in the actual transportation of oversized loads: the experiment confirms the author’s hypothesis. Based on the result of the experiment it is possible to state that a slightly modified UAS model can significantly influence the execution phase of the oversized load movement in a positive way. It shows that the use of the model reduces the time of the movement and avoids unexpected interferences.

This article examines autonomous reconnaissance in a complex urban environment using unmanned aerial vehicles (UAVs). Environments with many buildings and other types of obstacles and/or an uneven terrain are harder to be explored as occlusion of objects of interest may often occur. First, in this article, the problem of autonomous reconnaissance in a complex urban environment via a swarm of UAVs is formulated. Then, the algorithm based on the metaheuristic approach is proposed for a solution. This solution lies in deploying a number of waypoints in the area of interest to be explored, from which the monitoring is performed, and planning the routes for available UAVs among these waypoints so that the monitored area is as large as possible and the operation as short as possible. In the last part of this article, two types of main experiments based on computer simulations are designed to verify the proposed algorithms. The first type focuses on comparing the results achieved on the benchmark instances with the optimal solutions. The second one presents and discusses the results obtained from a number of scenarios, which are based on typical reconnaissance operations in real environments.

In recent years, the use of modern technology in military operations has become standard practice. Unmanned systems play an important role in operations such as reconnaissance and surveillance. This article examines a model for planning aerial reconnaissance using a fleet of mutually cooperating unmanned aerial vehicles to increase the effectiveness of the task. The model deploys a number of waypoints such that, when every waypoint is visited by any vehicle in the fleet, the area of interest is fully explored. The deployment of waypoints must meet the conditions arising from the technical parameters of the sensory systems used and tactical requirements of the task at hand. This paper proposes an improvement of the model by optimizing the number and position of waypoints deployed in the area of interest, the effect of which is to improve the trajectories of individual unmanned systems, and thus increase the efficiency of the operation. To achieve this optimization, a modified simulated annealing algorithm is proposed. The improvement of the model is verified by several experiments. Two sets of benchmark problems were designed: (a) benchmark problems for verifying the proposed algorithm for optimizing waypoints, and (b) benchmark problems based on typical reconnaissance scenarios in the real environment to prove the increased effectiveness of the reconnaissance operation. Moreover, an experiment in the SteelBeast simulation system was also conducted.

The article deals with modern technologies to support military operations in order to yield new innovations and development in the area of security and sustainability of military units. The article is divided into two key parts. The first part presents the model of the Autonomous Aerial Reconnaissance Problem (AARP). Firstly, the basic features and principles of the model are discussed. The AARP can be seen as a well-known Multi-Depot Vehicle Routing Problem (MDVRP); however, the different optimal criterion is used. Thus, the AARP is formulated for the first time as a new problem. Then, the basic aspects of the original metaheuristic solution proposed by the authors to the AARP is introduced. Finally, the algorithm is verified on the benchmark instances to show its effectiveness. The second key part of the article deals with the tactical aspects of the AARP; the use of the model is shown on the platoon level within a chosen tactical activity.

This paper presents experiment of the Tactical Decision Support System (TDSS) implementation within company defensive operation. TDSS system fully integrates model of aerial reconnaissance, which significantly influence decision-making of the company commander during the defensive operation. The experiment was conducted with support of simulation technology, particularly Steel Beast Pro software. As a part of various scenarios the paper presents results of UAS reconnaissance model use within different scenario on tactical level. The key part of this article defines parameters of the experiment, evaluates the results and confirms the purpose of the model in support of the decision-making process of a commander. The paper also deals with impact of usage modern technology on decision-making process.

This paper presents experiments with the model of aerial reconnaissance in the real environment. The model has been integrated into the Tactical Decision Support System (TDSS) which supports commanders of the Czech Army in their decision-making. The model is focused on planning the optimal reconnaissance operation of the area of interest by a fleet of unmanned aerial systems (UASs). A set of experiments on various scenarios has been proposed to verify the model in the real environment. The key part of this article defines parameters of the experiments, evaluates the results and confirms the purpose of the model in support of the decision making process of a commander. The paper also deals with other possibilities of using the model in the area of chemical, biological, radiological and nuclear defense (CBRN).