145 citations · 814 across the 26 of their papers we have counts for
29 papers
Deep Reinforcement Learning for Weapons to Targets Assignment in a Hypersonic strike
Brian Gaudet, Kris Drozd, Roberto Furfaro
We use deep reinforcement learning (RL) to optimize a weapons to target assignment (WTA) policy for multi-vehicle hypersonic strike against multiple targets. The objective is to ma…
Photometric Characterization and Trajectory Accuracy of Starlink Satellites: Implications for Ground-Based Astronomical Surveys
Grace Halferty, Vishnu Reddy, Tanner Campbell +2
Starlink is a low-Earth orbit (LEO) satellite constellation operated by Space Exploration Technologies Corp. (SpaceX) which aims to provide global satellite internet access. Thus f…
Line of Sight Curvature for Missile Guidance using Reinforcement Meta-Learning
Brian Gaudet, Roberto Furfaro
We use reinforcement meta learning to optimize a line of sight curvature policy that increases the effectiveness of a guidance system against maneuvering targets. The policy is imp…
Extracting Space Situational Awareness Events from News Text
Zhengnan Xie, Alice Saebom Kwak, Enfa George +5
Space situational awareness typically makes use of physical measurements from radar, telescopes, and other assets to monitor satellites and other spacecraft for operational, naviga…
Integrated Guidance and Control for Lunar Landing using a Stabilized Seeker
Brian Gaudet, Roberto Furfaro
We develop an integrated guidance and control system that in conjunction with a stabilized seeker and landing site detection software can achieve precise and safe planetary landing…
Breaking the Barrier for Minimum -cut on Simple Graphs
Zhiyang He, Jason Li
In the minimum -cut problem, we want to find the minimum number of edges whose deletion breaks the input graph into at least connected components. The classic algorithm of K…
Terminal Adaptive Guidance for Autonomous Hypersonic Strike Weapons via Reinforcement Learning
Brian Gaudet, Roberto Furfaro
An adaptive guidance system suitable for the terminal phase trajectory of a hypersonic strike weapon is optimized using reinforcement meta learning. The guidance system maps observ…
Integrated and Adaptive Guidance and Control for Endoatmospheric Missiles via Reinforcement Learning
Brian Gaudet, Roberto Furfaro
We apply a reinforcement meta-learning framework to optimize an integrated and adaptive guidance and flight control system for an air-to-air missile. The system is implemented as a…
Adaptive Approach Phase Guidance for a Hypersonic Glider via Reinforcement Meta Learning
Brian Gaudet, Kris Drozd, Ryan Meltzer +1
We use Reinforcement Meta Learning to optimize an adaptive guidance system suitable for the approach phase of a gliding hypersonic vehicle. Adaptability is achieved by optimizing o…
The Effect of Inefficient Accretion on Planetary Differentiation
Saverio Cambioni, Seth A. Jacobson, Alexandre Emsenhuber +5
Pairwise collisions between terrestrial embryos are the dominant means of accretion during the last stage of planet formation. Hence, their realistic treatment in N-body studies is…
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…
Extreme Theory of Functional Connections: A Physics-Informed Neural Network Method for Solving Parametric Differential Equations
Enrico Schiassi, Carl Leake, Mario De Florio +3
In this work we present a novel, accurate, and robust physics-informed method for solving problems involving parametric differential equations (DEs) called the Extreme Theory of Fu…
Reinforcement Meta-Learning for Interception of Maneuvering Exoatmospheric Targets with Parasitic Attitude Loop
Brian Gaudet, Roberto Furfaro, Richard Linares +1
We use Reinforcement Meta-Learning to optimize an adaptive integrated guidance, navigation, and control system suitable for exoatmospheric interception of a maneuvering target. The…
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…
Fuel-Efficient Powered Descent Guidance on Large Planetary Bodies via Theory of Functional Connections
Hunter Johnston, Enrico Schiassi, Roberto Furfaro +1
In this paper we present a new approach to solve the fuel-efficient powered descent guidance problem on large planetary bodies with no atmosphere (e.g. the Moon or Mars) using the…
Realistic On-the-fly Outcomes of Planetary Collisions II: Bringing Machine Learning to N-body Simulations
Alexandre Emsenhuber, Saverio Cambioni, Erik Asphaug +3
Terrestrial planet formation theory is at a bottleneck, with the growing realization that pairwise collisions are treated far too simply. Here, and in our companion paper (Cambioni…
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…
Six Degree-of-Freedom Body-Fixed Hovering over Unmapped Asteroids via LIDAR Altimetry and Reinforcement Meta-Learning
Brian Gaudet, Richard Linares, Roberto Furfaro
We optimize a six degrees of freedom hovering policy using reinforcement meta-learning. The policy maps flash LIDAR measurements directly to on/off spacecraft body-frame thrust com…
Seeker based Adaptive Guidance via Reinforcement Meta-Learning Applied to Asteroid Close Proximity Operations
Brian Gaudet, Richard Linares, Roberto Furfaro
Current practice for asteroid close proximity maneuvers requires extremely accurate characterization of the environmental dynamics and precise spacecraft positioning prior to the m…
Reinforcement Learning for Angle-Only Intercept Guidance of Maneuvering Targets
Brian Gaudet, Roberto Furfaro, Richard Linares
We present a novel guidance law that uses observations consisting solely of seeker line of sight angle measurements and their rate of change. The policy is optimized using reinforc…
Adaptive Guidance and Integrated Navigation with Reinforcement Meta-Learning
Brian Gaudet, Richard Linares, Roberto Furfaro
This paper proposes a novel adaptive guidance system developed using reinforcement meta-learning with a recurrent policy and value function approximator. The use of recurrent netwo…
Realistic On-The-Fly Outcomes of Planetary Collisions: Machine Learning Applied to Simulations of Giant Impacts
Saverio Cambioni, Erik Asphaug, Alexandre Emsenhuber +3
Planet formation simulations are capable of directly integrating the evolution of hundreds to thousands of planetary embryos and planetesimals, as they accrete pairwise to become p…
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…