slam

pose estimation

pose

human pose

anammox process

food enzyme

radiochemical

pose_50338

on-orbit

spinal_46972

non-cooperative

ficoll

branches

human pose estimation

object pose

cooperative_133689

right-wing

videos mission improve

camera pose

secondary school

On-orbit proximity operations in space rendezvous, docking and debris removal require precise and robust 6D pose estimation under a wide range of lighting conditions and against highly textured background, i.e., the Earth.This paper investigates leveraging deep learning and photorealistic rendering for monocular pose estimation of known uncooperative spacecraft. We first present a simulator built on Unreal Engine 4, named URSO, to generate labeled images of spacecraft orbiting the Earth, which can be used to train and evaluate neural networks.Secondly, we propose a deep learning framework for pose estimation based on orientation soft classification, which allows modelling orientation ambiguity as a mixture model. This framework was evaluated both on URSO datasets and the European Space Agency pose estimation challenge. In this competition, our best model achieved 3rd place on the synthetic test set and 2nd place on the real test set. Moreover, our results show the impact of several architectural and training aspects, and we demonstrate qualitatively how models learned on URSO datasets can perform on real images from space.

Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering