Vision-based Terrain Relative Navigation for Planetary Landing
Graeme E. Sutterlin, Roshan T. Eapen · 2023
In this paper, the math involved in pose estimation is presented and examined. This work aims to determine pose (orientation and translation) based on the finding the correspondence between features in a image and a 3D points in the terrain frame using nonlinear least-squares method implemented through MATLAB’s fSolve function. The use of Gazebo as a physics simulator to produce an exact lighting environment and simulate the descent of a camera-equipped satellite on a parabolic approach to the crater is also covered in detail. The challenges posed by sensor limitations and camera noise are also mentioned. It is shown that the nonlinear least-squares is able to accurately estimate the pose up to machine precision in the case without any noise, and up to a reasonable tolerance in the presence of noise. Monte-Carlo simulations are performed to validate these results.