Cone Index Estimation with Spectral Images Considering Poses of Light Source and Camera with Respect to Ground Surface

Abstract

In unmanned construction for landslide recovery, it is important to know the strength of the ground to prevent construction machinery from getting stuck due to the softness of the ground. However, a problem with wide-range ground strength estimation in previous studies is that unevenness and inclination variation of the surface can reduce the accuracy of the estimation, so this study aims to propose a cone index estimation method that is robust to unevenness and inclination variation. The proposed method uses a reflectance model to estimate spectral reflectance from spectral images considering the poses of the light source and the camera with respect to the ground surface, and then estimates the cone index from this spectral reflectance. The results of indoor validation experiments confirm the effectiveness of the proposed method.