activity
20192023
most citedDeep Learning-based Spacecraft Relative Navigation Methods: A Survey

107 citations · 195 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2023

Orbital AI-based Autonomous Refuelling Solution

Duarte Rondao, Lei He, Nabil Aouf

Cameras are rapidly becoming the choice for on-board sensors towards space rendezvous due to their small form factor and inexpensive power, mass, and volume costs. When it comes to…

cs.CV2023★ 1 cited

TransPose: A Transformer-based 6D Object Pose Estimation Network with Depth Refinement

Mahmoud Abdulsalam, Nabil Aouf

As demand for robotics manipulation application increases, accurate vision-based 6D pose estimation becomes essential for autonomous operations. Convolutional Neural Networks (CNNs…

cs.LG2022★ 3 cited

Explainability in Deep Reinforcement Learning, a Review into Current Methods and Applications

Thomas Hickling, Abdelhafid Zenati, Nabil Aouf +1

The use of Deep Reinforcement Learning (DRL) schemes has increased dramatically since their first introduction in 2015. Though uses in many different applications are being found,…

cs.LG2022★ 3 cited

Robust Adversarial Attacks Detection based on Explainable Deep Reinforcement Learning For UAV Guidance and Planning

Thomas Hickling, Nabil Aouf, Phillippa Spencer

The dangers of adversarial attacks on Uncrewed Aerial Vehicle (UAV) agents operating in public are increasing. Adopting AI-based techniques and, more specifically, Deep Learning (D…

cs.CV2021★ 9 cited

Real-time multiview data fusion for object tracking with RGBD sensors

Abdenour Amamra, Nabil Aouf

This paper presents a new approach to accurately track a moving vehicle with a multiview setup of red-green-blue depth (RGBD) cameras. We first propose a correction method to elimi…

cs.CV2021★ 6 cited

GPU based GMM segmentation of kinect data

Abdenour Amamra, Tarek Mouats, Nabil Aouf

This paper presents a novel approach for background/foreground segmentation of RGBD data with the Gaussian Mixture Models (GMM). We first start by the background subtraction from t…