Estimating the pose of an uncooperative spacecraft is an important computer vision problem
for enabling the deployment of automatic vision-based systems in orbit, with applications …

Object pose estimation is a core perception task that enables, for example, object
manipulation and scene understanding. The widely available, inexpensive, and high …

Abstract This work presents Spacecraft Pose Network v2 (SPNv2), a Convolutional Neural
Network (CNN) for pose estimation of noncooperative spacecraft across domain gap. SPNv2 …

This paper presents a neural-network-based unscented Kalman filter (UKF) to estimate and
track the pose (ie, position and orientation) of a known, noncooperative, tumbling target …

This work presents an Online Supervised Training (OST) method to enable robust vision-
based navigation about a non-cooperative spacecraft. Spaceborne Neural Networks (NN) …

This paper introduces an adaptive Convolutional Neural Network (CNN)-based Unscented
Kalman Filter for the pose estimation of uncooperative spacecraft. The validation is carried …

Autonomous spacecraft relative navigation via monocular images became a hot topic in the
past few years and, recently, received a further push thanks to the constantly growing field of …

While novel artificial intelligence and machine learning techniques are evolving and
disrupting established terrestrial technologies at an unprecedented speed, their adaptation …

Abstract Real-time 6 Degree-of-Freedom (DoF) pose estimation is of paramount importance
for various on-orbit tasks. Benefiting from the development of deep learning, Convolutional …

The use of deep learning (DL) algorithms has improved the performance of vision‐based
space applications in recent years. However, generating large amounts of annotated data …