ASSET

ASSET (Astrodynamics Software and Science Enabling Toolkit) is a modular, extensible library for trajectory design and optimal control. It uses a custom implementation of vector math formalisms to enable rapid implementation of dynamical systems and automatic differentiation. The phase object is the core of the optimal control functionality, and by linking multiple phases together, the user can construct scenarios of arbitrary complexity. A newly developed high performance interior-point optimizer (PSIOPT) is included with the library, which enables quick turnaround from concept to solution. ASSET is open source and developed by the Astrodynamics and Research Laboratory under Principal Investigator Dr. Rohan Sood.

Training Videos, Source Code, and Documentation

A comprehensive training delivered to Marshall Space Flight Center by ASRL’s Aaron Houin is publicly available here: Training. The full ASSET source code and documentation can be found on the ASRL GitHub.

Use Cases

A Delta 3 Multi Phase Optimal GTO Transfer, optimized in ASSET.
A heteroclinic connection between a 9:2 L2 Southern NRHO and a 9:2 L2 Northern NRHO optimized in ASSET
A solar-sail enabled transfer trajectory to Sun-Earth L1. Optimized end-to-end in ASSET!
A low-thrust enabled LEO to MEO transfer trajectory, optimized in ASSET.
A low-thrust enabled trajectory from a 9:2 L2 Southern NRHO to a 4:1 L2 Southern NRHO, optimized to deliver maximum CubeSat mass in ASSET.

Relevant Publications

  1. J. Pezent, “On the Implementation and Applications of a High Performance Trajectory Optimization Toolkit,” Ph.D., May 2024.
  2. Pezent, J.B., Sikes, J.D., Sood, R., Howell, K.C., and Stuart, J., 2023, August. Enhancements to the Astrodynamics Software and Science Enabling Toolkit (ASSET). In 2023 AAS/AIAA Astrodynamics Specialist Conference (23-326).
  3. Pezent, J.B., Sikes, J.D., Ledbetter, W.G., Sood, R., Howell, K.C., and Stuart, J., 2022, January. ASSET: Astrodynamics Software and Science Enabling Toolkit. In 32nd AIAA/AAS Space Flight Mechanics Meeting (p. 1131). DOI: https://doi.org/10.2514/6.2022-1131.​