Three-Dimensional Path Planning of Unmanned Aerial Vehicles Using Particle Swarm Optimization

Foo, Jung
Knutzon, Jared
Oliver, James
Winer, Eliot
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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 while simultaneously minimizing fuel consumption. The initial design point is a straight path between the current position and the desired target. Using PSO, an optimized path is generated through B-spline curves. The resulting paths can be optimized with a preference towards maximum safety, minimum fuel consumption or a combination of the two. The problem formulation and solution implementation is described along with the results from several simulated scenarios.


This is a conference proceeding from AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference (2006): 1, doi:10.2514/6.2006-6995. Posted with permission.

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