65 Publications (Page 1 of 3)
2024
Analyzing Data-Driven CR3BP Orbit Representations for Immersive Astrodynamics Catalogs. AIAA SCITECH 2024 Forum
 
Structure of the NRHO-to-LLO Abort Trajectory Design Space. AIAA SCITECH 2024 Forum
 
Transformer-based anomaly detection in P-LEO constellations: A dynamic graph approach. Acta Astronautica
. | Journal Article
2023
Anomaly Detection in P-LEO Constellations: a Dynamic Graph Approach. Acta Astronautica
. | Journal Article
 
A Table-Top Game to Simulate Competition between P-LEO Satellite Internet Constellations. Astrodynamics Specialist Conference, Big Sky, MT
 
Coevolving Defender Strategies Within Adversarial Ground Station Transit Time Games via Competitive Coevolution. The Journal of the Astronautical Sciences
. | Journal Article
 
Comparison of Learning Spacecraft Path-Planning Solutions from Imitation in Three-Body Dynamics. Journal of Spacecraft and Rockets
. | Journal Article
 
Quantifying hinge torque in self-folding, shape memory polymer origami under varying thermal loads. Applied Materials Today
. | Journal Article
2022
Coevolving Defender Strategies within Adversarial Ground Station Transit Time Games via Competitive Coevolution
 
Feasibility Studies for an Autonomous Cislunar Position, Navigation and Timing Constellation. Astrodynamics Specialist Conference, Charlotte, NC, August 2022
 
Graph neural networks for simulating crack coalescence and propagation in brittle materials
Perera, Roberto⋅Perera, R.⋅Guzzetti, Davide⋅Guzzetti, D.⋅Agrawal, V. and Agrawal, Vinamra
 
Modeling and Gamification Framework of Business Competition between P-LEO Constellations
 
Satellite Tycoon: Modeling Economic Competition in the Business of P-LEO Constellations
2021
AN ASSESSMENT OF VIRTUAL REALITY TECHNOLOGY FOR ASTRODYNAMICS APPLICATIONS
Guzzetti, D.⋅Somavarapu, D.H. and Turner, G.
(pp. 4775-4794)
 
AUTONOMOUS SMALL BODY GRAVIMETRY VIA A2C PATH-PLANNING
Indaco, M.⋅Lavagna, M. and Guzzetti, D.
(pp. 1741-1759)
 
DEEP REINFORCEMENT LEARNING TO ENHANCE FLY-AROUND GUIDANCE FOR UNCOOPERATIVE SPACE OBJECTS SMART IMAGING
Brandonisio, A.⋅Lavagna, M. and Guzzetti, D.
(pp. 211-230)
 
Graph neural networks for simulating crack coalescence and propagation in brittle materials
Perera, R.⋅Guzzetti, D. and Agrawal, V.
 
Interactive imitation learning for spacecraft path-planning in binary asteroid systems
Parmar, K. and Guzzetti, D.
(pp. 1928-1951)
 
Introducing Chaos in Elementary School; a Precursor for Multibody Dynamics
Busato, J.E.⋅Miskioglu, E.⋅Martin, K.M. and Guzzetti, D.
 
Optimized and autonomous machine learning framework for characterizing pores, particles, grains and grain boundaries in microstructural images
Perera, R.⋅Guzzetti, D. and Agrawal, V.
 
Optimized and autonomous machine learning framework for characterizing pores, particles, grains and grain boundaries in microstructural images
Perera, Roberto⋅Perera, R.⋅Guzzetti, Davide⋅Guzzetti, D.⋅Agrawal, V. and Agrawal, Vinamra
 
Reinforcement Learning for Uncooperative Space Objects Smart Imaging Path-Planning
Brandonisio, A.⋅Lavagna, M. and Guzzetti, D.
(pp. 1145-1169)
 
Time-Varying Shadows of Quasi-Periodic Motion Across Sections of the Flow Within Nearly Time-Periodic Three-Body Dynamics
Guzzetti, D. and Baoyin, H.
(pp. 855-890)
 
Toward Co-Evolving Solutions of Adversarial Ground Stations Transit Time Games For P-LEO Constellation Management
 
Toward immersive spacecraft trajectory design: Mapping user drawings to natural periodic orbits
Somavarapu, D.H. and Guzzetti, D.
(pp. 208-221)