Shadow-Robust Silhouette Reconstruction for Small-Body Applications

Abstract

Small bodies’ exploration highlighted the need to develop new algorithms for deep space probes navigation. The estimation of the small-body shape is a crucial step for relative navigation, mission planning, and gravity investigation. This paper develops a shape from silhouette algorithm that takes as input a series of images to construct a polyhedral shape for small bodies of the solar system. First, the silhouette associated with the visible part of the body is extracted and modified to account for shadowing effects. Second, the shape is computed by intersecting the viewing cones, i.e., the cone whose apex is the camera center and whose vertices are the silhouette points. The algorithm output is a polyhedral shape whose reconstruction is robust to shadowing. The algorithm is validated by reconstructing the shape of Itokawa and Bennu from synthetic images simulated with Airbus Defence & Space’s rendering engine SurRender™. Moreover, the algorithm is tested on real images from Hayabusa’s approach. Results prove the capability to provide an efficient shape reconstruction for small-body applications.