Three-dimensional UAS Trajectory Optimization for Remote Sensing in an Irregular Terrain Environment

This paper presents a novel algorithm for three-dimensional UAS trajectory optimization for a remote sensing mission in an irregular terrain environment. The algorithm consists of three steps: terrain modeling, the selection of scanning waypoints, and trajectory optimization. The terrain modeling process obtains a functional model using a Gaussian process from terrain information with a point cloud. The next step defines scanning waypoints based on the terrain model information, sensor specifications, and the required image resolution. For the selection of the waypoints, this paper introduces two different approaches depending on the direction of the viewing angle: a normal offset method and a vertical offset method. In the trajectory optimization, the proposed algorithm solves a distance-constraint vehicle routing problem to identify the optimum scanning route based on the waypoints and UAS constraints. Numerical simulations are conducted with two different UAS trajectory scanning methods in a realistic scenario, Point Loma in San Diego.