Astrodynamics Software & Science Enabling Toolkit (ASSET) Overview

Discipline: Flight Mechanics

Abstract:
This presentation focused on the ASSET optimization tool developed by Rohan Sood and Aaron Houin at the University of Alabama, discussing its technical architecture, including a custom vector function auto-differentiation system and the PSYOP optimizer, which enables efficient large-scale trajectory optimization for space missions. The tool is primarily C++ under the hood but interfaces through Python, offering open-source accessibility and parallelization features for both integration and optimization tasks. Practical applications and use cases were shared, such as solar sail missions, lunar transfers, and generating training datasets for maneuver autonomy, with emphasis on adaptive mesh refinement, event detection, and handling complex mission phases. The discussion includes technical challenges like integrating high-fidelity ephemeris data, managing discontinuities in impulsive maneuvers, and the need for more user-friendly convenience functions, highlighting ongoing improvements and community feedback.