Professor of Systems and Industrial Engineering
Director, Space Situational Awareness
|Roberto Furfaro is currently Assistant Research Professor in the Aerospace and Mechanical Engineering Department, University of Arizona. He has a large spectrum of research interests, which includes neutron and photon computational transport, neural and fuzzy systems, space systems and micro-satellite design. Over thepast few years, he has been collaborating with Ecosystem Science and Technology branch at NASA Ames on the “NASA Coffee Project” in which he led the development of an intelligent algorithm for coffee ripeness prediction using UAV airborne images. He has had a long-term involvement with Mars exploration since 1998 when he joinedthe NASA SERC at University of Arizona to become the project manager for the development of two robotic devices designed to utilize Martian local resources. Recently, he has been working developing of novel engineering solutions for planetary exploration including fuzzy-based expert systems for autonomous life-searching in extraterrestrial bodies.|
- Picca, P., & Furfaro, R. (2017). Application of Extreme Learning Machines to inverse neutron kinetics. Annals of Nuclear Energy, 100, 1--8.
- Picca, P., & Furfaro, R. (2017). Application of the transport-driven diffusion approach for criticality calculations. Journal of Computational and Theoretical Transport, 46 (4), 258-282.
- Furfaro, R., Topputo, F., Mueting, J. R., Casotto, S., & Simo, J. (2016). Analysis and Performance Evaluation of the ZEM/ZEV Guidance and its Sliding Robustification for Autonomous Rendezvous in Relative Motion.
- Mueting, J., Furfaro, R., Topputo, F., & Simo, J. (2016). Optimal Sliding Guidance for Earth-Moon Halo Orbit Station-Keeping and Transfer.
- Picca, P., Furfaro, R., & Ganapol, B. D. (2016). Application of Non-Linear Extrapolations for the Convergence Acceleration of Source Iteration. Journal of Computational and Theoretical Transport, 45(5), 351--367.
- Schiassi, E., Furfaro, R., & Mostacci, D. (2016). Bayesian inversion of coupled radiative and heat transfer models for asteroid regoliths and lakes. Radiation Effects and Defects in Solids, 171(9-10), 736--745.
- Walls, R., Gaylor, D., Reddy, V., Furfaro, R., & Jah, M. (2016). Assessing the IADC Space Debris Mitigation Guidelines: A case for ontology-based data management. AMOS Paper.
- Wibben, D. R., & Furfaro, R. (2016). Optimal sliding guidance algorithm for Mars powered descent phase. Advances in Space Research, 57(4), 948--961.
- Wibben, D. R., & Furfaro, R. (2016). Terminal Guidance for Lunar Landing and Retargeting Using a Hybrid Control Strategy. Journal of Guidance, Control, and Dynamics, 1168--1172.
- Cersosimo, D., Bellerose, J., & Furfaro, R. (2013). Sliding guidance techniques for close proximity operations at multiple asteroid systems. AIAA Guidance, Navigation, and Control (GNC) Conference.
- Furfaro, R., Cersosimo, D., & Wibben, D. R. (2013). Asteroid precision landing via multiple sliding surfaces guidance techniques. Journal of Guidance, Control, and Dynamics, 36(4), 1075-1092.
- Furfaro, R., Gaudet, B., Wibben, D. R., & Simo, J. (2013). Development of non-linear guidance algorithms for asteroids close-proximity operations. AIAA Guidance, Navigation, and Control (GNC) Conference.
- Picca, P., & Furfaro, R. (2013). Analytical discrete ordinate method for radiative transfer in dense vegetation canopies. Journal of Quantitative Spectroscopy and Radiative Transfer, 118, 60-69.
- Adebonojo Jr., B. O., Cupples, M. L., Furfaro, R., & Kidd Jr., J. N. (2012). Launch analyses supporting conceptual human-precursor robotic asteroid missions. Advances in the Astronautical Sciences, 142, 579-594.
- Boscheri, G., Kacira, M., Patterson, L., Giacomelli, G., Sadler, P., Furfaro, R., Lobascio, C., Lamantea, M., & Grizzaffi, L. (2012). Modified energy cascade model adapted for a multicrop Lunar greenhouse prototype. Advances in Space Research, 50(7), 941-951.
- Furfaro, R. (2016, Fall). Mars-Lunar Greenhouse (M-LGH) Prototype For Bioregenerative Life Support Systems in Future Planetary Outposts. In 67th International Astronautical Conference, Guadalajara, Mexico..
- Furfaro, R., Linares, R., Gaylor, D., & Jah, M. (2016). Mapping Sensors Measurements to the Resident Space Objects Behavior Energy and State Parameters Space via Extreme Learning Machines. In 67th International Astronautical Conference, Guadalajara, Mexico.
- Furfaro, R., Linares, R., Gaylor, D., Jah, M., & Walls, R. (2016). Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks. In The Advanced Maui Optical and Space Surveillance Technologies Conference.
- Linares, R., & Furfaro, R. (2016). Dynamic Sensor Tasking for Space Situational Awareness via Reinforcement Learning. In Advanced Maui Optical and Space Surveillance Technologies Conference.
- Linares, R., & Furfaro, R. (2016). Space Object classification using deep Convolutional Neural Networks. In Information Fusion (FUSION), 2016 19th International Conference on.
- Furfaro, R. (2016, Spring). Mars-Lunar Greenhouse (M-LGH) Prototype at the University of Arizona: Status and Path Forward.. 7th International AgroSpace Workshop Mars – A Long Way to Go. Sperlonga (LT) [former] Santa Maria Church, May, 26th – 27th 2016.