LAUSR

Algorithms for fixed-wing unmanned aerial systems (UAS) must integrate on-board sensor capabilities and vehicle maneuver constraints to reliably satisfy the objectives of persistent surveillance, path planning, and trajectory management. In many cases, the characteristic dimensions of sensor fields of view are comparable with the turning radius of the UAS platform. Consequently, when persistent, full area, time-critical coverage is required and the number of assets is limited, the complexity of path planning is increased, as the turn radius becomes comparable with or exceeds the sensor footprint. A technique is developed to integrate persistent surveillance mission requirements with sensor resolution and field-of-view to facilitate efficient path planning. Graph search techniques and spline-based methods are combined to develop computationally simple algorithms that converge to feasible paths with $G^{2}$ continuity. ( $G^{2}$ continuity in this context means the path, which is constructed from a concatenated series of $C^{2}$ curve segments, and its derivatives are continuous through two derivatives, but the magnitudes of second derivatives may differ at the boundaries, where these curve segments are joined to form the entire path. Curvature is continuous throughout.) Two example cases are provided. In the first, the turning radius is small in comparison with the sensor footprint, while in the second, the minimum turn radius is a critical parameter in the determination of a feasible path.