UAV Mission Planning with SAR Application The paper presents the concept of mission planning for a shortrange tactical class Unmanned Aerial Vehicle (UAV) that recognizes targets using the sensors it has been equipped with. Tasks carried out by such systems are mainly associated with aerial reconnaissance employing Electro Optical (EO)Near InfraRed (NIR) heads, Synthetic Aperture Radar (SAR), and Electronic Intelligence (ELINT) systems. UAVs of this class are most often used in NATO armies to support artillery actions, etc. The key task, carried out during their activities, is to plan a reconnaissance mission in which the flight route will be determined that optimally uses the sensorsxe2x80x99 capabilities. The paper describes the scenario of determining the mission plan and, in particular, the UAV flight routes to which the recognition targets are assigned. The problem was decomposed into several subproblems: assigning reconnaissance tasks to UAVs with choosing the reconnaissance sensors and designating an initial UAV flight plan. The last step is planning a detailed flight route taking into account the time constraints imposed on recognition and the characteristics of the reconnaissance sensors. The final step is to generate the real UAV flight trajectory based on its technical parameters. The algorithm for determining exact flight routes for the indicated reconnaissance purposes was also discussed, taking into account the presence of enemy troops and available air corridors. The task scheduling algorithmxe2x80x94Vehicle Route Planning with Time Window (VRPTW)xe2x80x94using time windows is formulated in the form of the Mixed Integer Linear Problem (MILP). The MILP formulation was used to solve the UAV flight route planning task. The algorithm can be used both when planning individual UAV missions and UAV groups cooperating together. The approach presented is a practical way of establishing mission plans implemented in real unmanned systems.

Occlusionaware UAV Path Planning for Reconnaissance and Surveillance in Complex Environments This paper concerns the reconnaissance and surveillance problem for multirotor aerial drones or unmanned aerial vehicles (UAVs) flying over geometrically complex environments, such as mountainous terrains and urban regions. In contrast to the existing literature, our approach takes both UAV kinematics constraints and camera sensing constraints into consideration. We present a twostage strategy to solve this UAV surveillance problem with the given terrain information. In the first stage, the challenge is to find a set of camera locations called the vantage waypoint set to provide full coverage of the area of interest, which can be viewed as a 3D Art Gallery Problem using drones as the observers. In the second stage, one or several UAVs are determined to conduct the full coverage reconnaissance and surveillance duty along individual routes respecting their kinematic constraints in the optimization criterion (the shortest time possible). This variant of the combinatorial traveling salesman problem is solved by introducing unsupervised learning and Bezier curves. The reported results support the feasibility of the proposed solution.