Three Dimensional Multi-Objective UAV Path Planning Using Digital Pheromone Particle Swarm Optimization

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 aircraft or enemy threats. Often automated path planning algorithms are employed to specify targets for a UAV to investigate. To date, path-planning algorithms have been limited to providing only a single solution (alternate path) without further input from a pilot. This paper uses digital pheromones to improve upon a previously developed multi-objective path planner that uses Particle Swarm Optimization (PSO) to generate multiple solution paths based on predefined criteria. The problem formulation is designed to minimize risk due to enemy threats and fuel consumption while maximizing reconnaissance and eliminating terrain violations. The implementation of digital pheromone PSO increases the efficiency and reliability of paths returned to the operator. The decrease in iterations allows alternate paths to be returned in real time, aiding in efficient decision making by the UAV operator. The implementation of Digital Pheromone PSO is described below along with the results of simulated scenarios.