11 papers
Simulation Based Reward Function Validation for Multi-Agent On Orbit Inspection
Patrick Quinn, Bala Prenith Reddy Gopu, George M. Nehma +1
A proposed method for the control of groups of inspection spacecraft is Multi-Agent Reinforcement Learning (MARL). While MARL has already been employed for this purpose in previous…
From Images2Mesh: A 3D Surface Reconstruction Pipeline for Non-Cooperative Space Objects
Bala Prenith Reddy Gopu, Patrick Quinn, George M. Nehma +4
On-orbit inspection imagery is crucial as it enables characterization of non-cooperative resident space objects, providing the geometry and structural condition essential for activ…
Dynamic Scene 3D Reconstruction of an Uncooperative Resident Space Object
Bala Prenith Reddy Gopu, Timothy Jacob Huber, George M. Nehma +5
Characterization of uncooperative Resident Space Objects (RSO) play a crucial role in On-Orbit Servicing (OOS) and Active Debris Removal (ADR) missions to assess the geometry and m…
Real-time Testing of Satellite Attitude Control With a Reaction Wheel Hardware-In-the-Loop Platform
Morokot Sakal, George Nehma, Camilo Riano-Rios +1
We propose the Hardware-in-the-Loop (HIL) test of an adaptive satellite attitude control system with reaction wheel health estimation capabilities. Previous simulations and Softwar…
Physics-Informed EvolveGCN: Satellite Prediction for Multi Agent Systems
Timothy Jacob Huber, Madhur Tiwari, Camilo A. Riano-Rios
In the rapidly evolving domain of autonomous systems, interaction among agents within a shared environment is both inevitable and essential for enhancing overall system capabilitie…
Adaptive Controller For Simultaneous Spacecraft Attitude Tracking And Reaction Wheel Fault Detection
Camilo Riano-Rios, George Nehma, Madhur Tiwari
The attitude control of a spacecraft is integral to achieving mission success. However, failures in actuators such as reaction wheels are detrimental and can often lead to an early…
End-to-End Imitation Learning for Optimal Asteroid Proximity Operations
Patrick Quinn, George Nehma, Madhur Tiwari
Controlling spacecraft near asteroids in deep space comes with many challenges. The delays involved necessitate heavy usage of limited onboard computation resources while fuel effi…
Dwellers in the Deep: Biological Consequences of Dark Oxygen
Manasvi Lingam, Amedeo Balbi, Madhur Tiwari
The striking recent putative detection of "dark oxygen" (dark O) sources on the abyssal ocean floor in the Pacific at km depth raises the intriguing scenario that comp…
Leveraging KANs For Enhanced Deep Koopman Operator Discovery
George Nehma, Madhur Tiwari
Multi-layer perceptrons (MLP's) have been extensively utilized in discovering Deep Koopman operators for linearizing nonlinear dynamics. With the emergence of Kolmogorov-Arnold Net…
Deep Learning Based Dynamics Identification and Linearization of Orbital Problems using Koopman Theory
George Nehma, Madhur Tiwari, Manasvi Lingam
The study of the Two-Body and Circular Restricted Three-Body Problems in the field of aerospace engineering and sciences is deeply important because they help describe the motion o…
Computationally Efficient Data-Driven Discovery and Linear Representation of Nonlinear Systems For Control
Madhur Tiwari, George Nehma, Bethany Lusch
This work focuses on developing a data-driven framework using Koopman operator theory for system identification and linearization of nonlinear systems for control. Our proposed met…