Spatiotemporal scenario data-driven decision for the path planning of multiple UASs

Abstract

Modern systems operate in spaiotemporally evolving environments, and similar spatiotemporal scenarios are likely to be tied with similar decision solutions. This paper develops a spatiotemporal scenario data-driven decision solution for the path planning of multiple unmanned aircraft systems (UASs) in wind fields. The solution utilities offline operations, online operations and sptaiotemporal scenario data queries to provide an efficient path planning decision for multiple UASs. The solution features the use of similarity between spatiotemporal scenarios to retrieve offline decisions as the initial solution for online fine tuning, which significantly shortens the online decision time. A fast query algorithm that exploits the correlation of spatiotemporal scenarios is utilized in the decision framework to quickly retrieve the best offline decisions. The solution is demonstrated using simulation studies, and can be utilized in other decision applications where spaiotemporal environments play a crucial role in the decision process and the allowed decision time window is short.