Projects

Online Supervised Training of Spaceborne Vision during Proximity Operations using Adaptive Kalman Filtering
This work presents an Online Supervised Training (OST) method to enable robust vision-based navigation about a non-cooperative spacecraft. Spaceborne Neural Networks (NN) are susceptible to domain gap as they are primarily trained with synthetic images due to the inaccessibility of space. OST aims to close this gap by training a pose estimation NN online using incoming flight images during ... [Read more]

SHIRT: Satellite Hardware-In-the-loop Rendezvous Trajectories Dataset
Deploying deep learning models into space missions is difficult due to the scarcity of real-life data from space. Particularly in spaceborne computer vision applications, while training can rely on synthetic data from computer renderers, the validation of the trained neural networks remains a big challenge. Our SPEED+ dataset addressed this challenge by introducing Hardware-In-the-Loop (HIL) images ... [Read more]