Three-Dimensional Multi-Objective UAV Path Planner Using Meta-Paths for Decision Making and Visualization

Abstract

Military operati ons are turning to more complex and advanced automation technolog y for mini mum risk and maximum efficiency. A critical piece to this strategy is unmanned aeri al vehicles (UAVs). UAVs require the intelligence to safely maneuver along a path to an intended target, avoi ding obstacles such as other aircrafts or enemy threats. Often automated path planning algori thms are employed to s pecify targets for a UAV to fl y to. To date, path-pl anning alg orithms have been limi ted to provi ding only a single solution (alternate) path without further inputs from the UAV controller. This paper presents a uni que platform for decision making in a three-di mensional path pl anner where mul ti ple solution paths are generated in the form of meta-paths. The path pl anner uses Particle Swarm Optimizati on (PSO) to generate multi ple solution paths based on predefined criteria. The problem formulati on was designed to mini mize risk due to enemy threats, to mini mize fuel consumption incurred by deviating from the original path, and takes into account reconnaissance targets. Using PSO, al ternate paths are generated using B -spline curves, optimized based on preferences set for the three objecti ves. The resulting paths can be optimized wi th a preference towards maxi mum safety, mini mum fuel co nsumpti on, or target reconnaissance. For each preference, the top fi ve solutions generated by PSO are presented, for a total of 15 alternate paths. In order to efficientl y present these multi ple solution paths, meta-paths are implemented, which is a single summarized representation of all the paths generated for a particular preference. This allows the decision making process to be completed in an efficient and organized manner. The problem formulati on and soluti on implementation is described along wi th the results from several simulated scenarios.