Roberto Furfaro, Ph.D.
Affiliations: | 2004 | University of Arizona, Tucson, AZ |
Area:
Aerospace Engineering, Remote Sensing, Agricultural EngineeringGoogle:
"Roberto Furfaro"Parents
Sign in to add mentor| Barry D. Ganapol | grad student | 2004 | University of Arizona | |
| (Radiative transport in plant canopies: Forward and inverse problem for UAV applications.) | ||||
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Publications
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| Emsenhuber A, Cambioni S, Asphaug E, et al. (2020) Realistic On-the-fly Outcomes of Planetary Collisions. II. Bringing Machine Learning to N-body Simulations The Astrophysical Journal. 891: 6 |
| Furfaro R, Barocco R, Linares R, et al. (2020) Modeling Irregular Small Bodies Gravity Field Via Extreme Learning Machines and Bayesian Optimization Advances in Space Research |
| Gaudet B, Linares R, Furfaro R. (2020) Deep reinforcement learning for six degree-of-freedom planetary landing Advances in Space Research. 65: 1723-1741 |
| Furfaro R, Scorsoglio A, Linares R, et al. (2020) Adaptive generalized ZEM-ZEV feedback guidance for planetary landing via a deep reinforcement learning approach Acta Astronautica. 171: 156-171 |
| Gaudet B, Linares R, Furfaro R. (2020) Terminal adaptive guidance via reinforcement meta-learning: Applications to autonomous asteroid close-proximity operations Acta Astronautica. 171: 1-13 |
| Furfaro R, Mortari D. (2020) Least-squares solution of a class of optimal space guidance problems via Theory of Connections Acta Astronautica. 168: 92-103 |
| Linares R, Furfaro R, Reddy V. (2020) Space Objects Classification via Light-Curve Measurements Using Deep Convolutional Neural Networks Journal of the Astronautical Sciences. 67: 1063-1091 |
| Cambioni S, Asphaug E, Emsenhuber A, et al. (2019) Realistic On-the-fly Outcomes of Planetary Collisions: Machine Learning Applied to Simulations of Giant Impacts The Astrophysical Journal. 875: 40 |
| Schiassi E, Furfaro R, Kargel JS, et al. (2019) GLAM Bio-Lith RT: A Tool for Remote Sensing Reflectance Simulation and Water Components Concentration Retrieval in Glacial Lakes Frontiers in Earth Science. 7 |
| Cambioni S, Delbo M, Ryan AJ, et al. (2019) Constraining the thermal properties of planetary surfaces using machine learning: Application to airless bodies Icarus. 325: 16-30 |