Motion planning for reduced observability of autonomous aerial vehicles

Abstract

Techniques originally developed for robot motion planning are applied to compute ingress paths for autonomous air vehicles, such as cruise missiles or uninhabited aerial vehicles (UAVs). This approach is particularly useful in multiobjective optimization problems such as intercepting a target while also maneuvering to minimize observability to ground-based tracking stations. Prescribing position and dimensional are chosen based on empirical measurements of the airframe's radar cross-section (RCS) as well as target state information. This six-degree-of-freedom motion planning formulation is an alternative to the traditional separation of guidance and autopilot functions and results in an unprecedented degree of guidance and control subsystem integration. This paper presents preliminary results and lays the groundwork for the development of future highly integrated guidance and control systems.