4 papers
Stereovision Image Processing for Planetary Navigation Maps with Semi-Global Matching and Superpixel Segmentation
Yan-Shan Lu, Miguel Arana-Catania, Saurabh Upadhyay +1
Mars exploration requires precise and reliable terrain models to ensure safe rover navigation across its unpredictable and often hazardous landscapes. Stereoscopic vision serves a…
A causal learning approach to in-orbit inertial parameter estimation for multi-payload deployers
Konstantinos Platanitis, Miguel Arana-Catania, Saurabh Upadhyay +1
This paper discusses an approach to inertial parameter estimation for the case of cargo carrying spacecraft that is based on causal learning, i.e. learning from the responses of th…
Spacecraft inertial parameters estimation using time series clustering and reinforcement learning
Konstantinos Platanitis, Miguel Arana-Catania, Leonardo Capicchiano +2
This paper presents a machine learning approach to estimate the inertial parameters of a spacecraft in cases when those change during operations, e.g. multiple deployments of paylo…
Autonomous Robotic Arm Manipulation for Planetary Missions using Causal Machine Learning
C. McDonnell, M. Arana-Catania, S. Upadhyay
Autonomous robotic arm manipulators have the potential to make planetary exploration and in-situ resource utilization missions more time efficient and productive, as the manipulato…