109 citations · 142 across the 5 of their papers we have counts for
5 papers
Physics-Informed Extreme Theory of Functional Connections Applied to Data-Driven Parameters Discovery of Epidemiological Compartmental Models
Enrico Schiassi, Andrea D'Ambrosio, Mario De Florio +2
In this work we apply a novel, accurate, fast, and robust physics-informed neural network framework for data-driven parameters discovery of problems modeled via parametric ordinary…
Adaptive Generalized ZEM-ZEV Feedback Guidance for Planetary Landing via a Deep Reinforcement Learning Approach
Roberto Furfaro, Andrea Scorsoglio, Richard Linares +1
Precision landing on large and small planetary bodies is a technology of utmost importance for future human and robotic exploration of the solar system. In this context, the Zero-E…
Space Objects Maneuvering Prediction via Maximum Causal Entropy Inverse Reinforcement Learning
Bryce Doerr, Richard Linares, Roberto Furfaro
Inverse Reinforcement Learning (RL) can be used to determine the behavior of Space Objects (SOs) by estimating the reward function that an SO is using for control. The approach dis…
Constraining the Thermal Properties of Planetary Surfaces using Machine Learning: Application to Airless Bodies
Saverio Cambioni, Marco Delbo, Andrew J. Ryan +2
We present a new method for the determination of the surface properties of airless bodies from measurements of the emitted infrared flux. Our approach uses machine learning techniq…
End to End Satellite Servicing and Space Debris Management
Aman Chandra, Himangshu Kalita, Roberto Furfaro +1
There is growing demand for satellite swarms and constellations for global positioning, remote sensing and relay communication in higher LEO orbits. This will result in many obsole…