MULTI-AGENT FLIGHT PLANNING IN A THREE-DIMENSIONAL THREAT ENVIRONMENT USING CROSS-ENTROPY SEARCH

Abstract

The multi-agent cross-entropy (CE) search method effectively optimizes flight routes in dynamic, contested three-dimensional (3D) environments where multiple aircraft must cooperate. Traditional military flight planning relies on pilots using complex and cumbersome software that lacks a comprehensive view of the operating environment. Surface-to-air threat weapon engagement zones (WEZs) are critical considerations in route planning, as excessive exposure can lead to mission failure, aircraft loss, or personnel endangerment. This thesis introduces a multi-agent CE-based path-finding approach that efficiently generates coordinated flight routes while optimizing factors such as route length and altitude and its deviations. For single-aircraft scenarios, where the path-finding problem satisfies the optimal substructure property (OSP), fast and optimal dynamic programming (DP) algorithms such as A* can be applied. However, multi-agent coordination violates OSP, making DP methods unsuitable. This research demonstrates that the CE search method can effectively navigate this complex problem space, producing near-optimal flight routes that balance the collective needs and objectives of multiple aircraft. Additionally, a novel evaluation framework is presented to assess the quality of CE-generated routes relative to the unattainable optimal solution.Distribution Statement A. Approved for public release: Distribution is unlimited.Major, United States Marine Corp