Spacecraft |

Omnicopters for Spacecraft Simulation

Wed, 01 May 2024 00:00:00 +0000

Senior design project and MS thesis component, funded by the LINCS Lab at the Air Force Research Laboratory ($5,000 CRADA award).

Omnicopters — multirotor vehicles with full 6-DOF control authority — were used to simulate spacecraft attitude and translation dynamics in a hardware-in-the-loop configuration. Key contributions:

Determined optimal motor placements and orientations for full controllability
Developed a novel control scheme for rejecting air disturbances in indoor environments
Validated the platform as a low-cost proxy for orbital spacecraft dynamics testing

Autonomous Spacecraft and Sensing

Mon, 01 Apr 2024 00:00:00 +0000

A systems-level demonstration of autonomous spacecraft operations, presented to a general audience and built entirely in the astrodynamics simulator.

Capabilities demonstrated:

Attitude correction and momentum management
Onboard debris detection via simulated optical sensor using an optical flow background removal scheme
Autonomous debris avoidance via thruster actuation
Cyber-attack simulation targeting autonomous operations with minimal detectability
Anomaly detection using LSTMs and isolation forests

Hall Thruster Design Optimization

Fri, 01 Mar 2024 00:00:00 +0000

Personal project combining plasma physics simulation with machine learning-guided design optimization.

Simulated 1D Hall thruster discharge and collected performance data across magnetic profile variations
Trained an adaptive neural surrogate model of the discharge dynamics
Jointly optimized thruster geometry and magnetic field profile to maximize efficiency

Detection of Debris from a Dynamic Satellite Platform

Thu, 01 Jun 2023 00:00:00 +0000

B. Outland, R. Loveland

Developed a novel debris detection algorithm for space-based optical sensors. Classical background-subtraction methods systematically remove faint, slow-moving objects — exactly the objects of interest in space domain awareness.

This approach uses an optical flow background removal scheme specifically designed to retain faint objects, followed by object detection classification. The method was validated on simulated imagery from a dynamic (tumbling/maneuvering) satellite observer.