1 citations · 1 across the 10 of their papers we have counts for
10 papers
AutoCause: A Python framework that automates expert decisions in environmental time-series causal discovery
Marco Ruiz, Miguel Arana-Catania, David R. Ardila +1
Environmental time-series causal discovery requires expert decisions about method choice, conditional-independence tests, lag horizons, sample-size adequacy, multiple-testing contr…
Causal-Audit: A Framework for Risk Assessment of Assumption Violations in Time-Series Causal Discovery
Marco Ruiz, Miguel Arana-Catania, David R. Ardila +1
Time-series causal discovery methods rely on assumptions such as stationarity, regular sampling, and bounded temporal dependence. When these assumptions are violated, structure lea…
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…
Parameter Estimation using Reinforcement Learning Causal Curiosity: Limits and Challenges
Miguel Arana-Catania, Weisi Guo
Causal understanding is important in many disciplines of science and engineering, where we seek to understand how different factors in the system causally affect an experiment or s…
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…
Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction
İrem Üstek, Miguel Arana-Catania, Alexander Farr +1
Wildfires pose a significantly increasing hazard to global ecosystems due to the climate crisis. Due to its complex nature, there is an urgent need for innovative approaches to wil…
Causal Reinforcement Learning for Optimisation of Robot Dynamics in Unknown Environments
Julian Gerald Dcruz, Sam Mahoney, Jia Yun Chua +4
Autonomous operations of robots in unknown environments are challenging due to the lack of knowledge of the dynamics of the interactions, such as the objects' movability. This work…
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…
Wind Estimation in Unmanned Aerial Vehicles with Causal Machine Learning
Abdulaziz Alwalan, Miguel Arana-Catania
In this work we demonstrate the possibility of estimating the wind environment of a UAV without specialised sensors, using only the UAV's trajectory, applying a causal machine lear…
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…