Military operations are turning to more complex and advanced automation technology for minimum risk and maximum efficiency. A critical piece to this strategy is unmanned aerial vehicles (UAVs). UAVs require the intelligence to safely maneuver along a path to an intended target, avoiding obstacles such as other aircrafts or enemy threats. Often automated path planning algorithms are employed to specify targets for a UAV to fly to. To date, path-planning algorithms have been limited to two-dimensional problem formulations. This paper presents a unique three-dimensional path planning problem formulation and solution approach using Particle Swarm Optimization (PSO). The problem formulation was designed to minimize risk due to enemy threats and also to minimize fuel consumption incurred by deviating from the original path. In addition, a third objective in the problem formulation takes into account reconnaissance targets. The initial design point is defined as the original path of the UAV. Using PSO, alternate paths are generated using B-spline curves, optimized based on preferences set for the three objectives. The resulting paths can be optimized with a preference towards maximum safety, minimum fuel consumption, or target reconnaissance. The problem formulation and solution implementation is described along with the results from several simulated scenarios.
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