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Astrodynamics Program

Spring 2026

1. Program Overview and Objectives

The Astrodynamics program develops the shared astrodynamics infrastructure that underpins the lab's research portfolio. Its role is to provide reliable, extensible, and well-documented computational tools that support both classical nonlinear dynamics analysis and modern learning-based representations of dynamical systems. The software produced by this program is intended to serve as foundational infrastructure upon which downstream autonomy, guidance, and machine learning projects depend.

The program's objectives are to establish a lightweight yet expressive astrodynamics codebase capable of generating, analyzing, and propagating nonlinear dynamical systems relevant to spaceflight. Particular emphasis is placed on standardizing workflows for orbit family generation, invariant manifold computation, uncertainty propagation, and control synthesis. A central goal is to enable large-scale, structured data generation suitable for training latent and reduced-order models, while simultaneously reducing duplicated effort across projects by providing a single, shared implementation of core capabilities. In this way, the program serves as a deliberate bridge between classical astrodynamics methods and learning-based modeling efforts across the lab.

This program is methodologically foundational and aligns primarily with 6.1-style research, but its outputs are explicitly designed to enable applied autonomy, guidance, and learning research across the lab.

2. Scope and Non-Goals

The scope of this program includes the development of core dynamical models, with an initial focus on the Circular Restricted Three-Body Problem and a clear path toward higher-fidelity extensions. The program covers orbit family generation and continuation, computation and propagation of stable and unstable manifolds, interfaces for uncertainty propagation and reachability analysis, and data generation pipelines intended to support learning-based methods. Visualization and post-processing tools that are tightly coupled to astrodynamics workflows are also within scope, provided they reinforce reuse and reproducibility.

Explicitly excluded from scope are mission-specific design studies, high-level autonomy logic or decision-making (which are owned by other programs), and monolithic mission analysis tools that are difficult to extend or test. One-off scripts or analyses without a clear path toward reuse or integration into shared infrastructure are also considered out of scope.

3. Core Deliverables for the First Semester

By the end of the semester, the program is expected to deliver a modular and well-structured astrodynamics software package, with CR3BP dynamics serving as the initial testbed. The codebase should define clear abstractions for dynamical systems, state representations, parameters, and propagators, and should maintain minimal but sufficient dependencies in order to remain lightweight and broadly reusable.

The initial implementation must support the generation of key orbit and invariant structure families, including periodic and quasi-periodic orbits, stable and unstable manifolds, and resonant orbits with continuation across resonances. These capabilities should be implemented using deterministic and reproducible methods, expose sensible defaults and parameterizations, and be validated against known results wherever feasible.

Although not all advanced capabilities must be fully implemented in the first semester, the architecture must explicitly support future extensions. These include uncertainty propagation and reachable set approximation, normal form–based and reduced-order analyses, control profile generation using both direct and indirect methods, and the export of ephemerides and trajectory data for downstream simulation, autonomy, and learning applications. The package should also support a curated library of canonical initial conditions and orbit families that allow users to rapidly initialize common analyses without re-deriving baseline results.

The software should include integrated visualization and analysis tools for inspecting orbits, manifolds, and phase-space structures, with support for generating high-quality figures and animations suitable for publications and presentations. A clear separation between numerical computation and visualization logic is expected.

Comprehensive documentation is a required deliverable. This includes a concise "getting started" guide for new students, tutorials demonstrating common workflows such as orbit family generation and manifold propagation, and design documentation that explains architectural decisions and intended extension points. In addition, the repository must include basic software quality infrastructure, including unit tests for core numerical routines, a continuous integration pipeline for automated testing and quality checks, and clearly defined coding standards and contribution guidelines.

4. User Stories and Intended Usage

The tools developed under this program should support a range of users with different levels of expertise and goals. A new group member should be able to generate a 9:2 resonant orbit and perform station-keeping analyses in the presence of perturbations such as solar radiation pressure without needing to reimplement low-level dynamics. A researcher developing latent models should be able to efficiently generate and propagate large ensembles of trajectories from invariant manifolds near equilibrium points, enabling data-driven approximation of dynamical boundaries. Researchers preparing publications or proposals should be able to generate clear, high-quality visualizations and animations of invariant structures. Undergraduate researchers should be able to run predefined scripts or notebooks to explore orbit families and dynamics without modifying core algorithms. Finally, senior developers and the PI should be able to trust that numerical results are reproducible, tested, and extensible.

5. Candidate Tasks and Work Breakdown

Over the course of the semester, the program is expected to define and execute a clear development roadmap for the astrodynamics package, including explicit definition of the MVP scope and near-term extensions. This includes selecting appropriate numerical methods and libraries, designing core abstractions for dynamical systems and orbit families, and implementing at least one complete end-to-end workflow that demonstrates the intended usage of the software from orbit generation through visualization.

Additional effort should be devoted to establishing a curated database of canonical initial conditions, developing data export pipelines suitable for machine learning workflows, writing tutorials and onboarding materials, and setting up testing and continuous integration infrastructure. Program members should also explicitly identify interfaces and dependencies with other lab programs to ensure alignment and reuse.

6. Collaboration, Meetings, and Workflow Expectations

Program members meet every two weeks for at least one hour on Fridays. These meetings are intended to support code and numerical result reviews, discussion of algorithmic choices and trade-offs, identification of missing functionality needed by other programs, and collective reading and discussion of relevant literature.

All substantive work is expected to occur through version-controlled workflows. Program members are responsible for filing issues and pull requests for their contributions, reviewing and commenting on each other's code, and actively using and stress-testing shared tools in their own research to expose usability and design issues early.

7. Faculty Interface and Code Review

At least once per semester, the program will conduct a structured design and code review with the PI. Program members should be prepared to present a concise overview of the software architecture, demonstrate representative workflows, and discuss known limitations, technical debt, and proposed next steps. This review is intended to provide senior-level feedback on design quality, extensibility, and long-term sustainability.

8. Undergraduate Integration and Mentorship

Program members are responsible for supervising undergraduate researchers aligned with this effort. Undergraduate work should primarily involve using existing workflows to generate and analyze orbit families, as well as contributing small extensions, tests, or visualization utilities. Graduate students are expected to ensure that tools are usable with minimal setup, provide clearly scoped tasks and documentation, and treat undergraduate engagement as a validation mechanism for usability, robustness, and documentation quality.

9. End-of-Semester Deliverables Checklist

By the conclusion of the Spring 2026 semester, the following items should be complete and verifiable. This checklist is intended to serve as a concrete assessment tool for program progress and maturity.

Repository and Architecture

  • A single, version-controlled astrodynamics repository designated as the program's canonical codebase.

  • Clearly defined core abstractions for dynamical systems, states, propagators, and orbit families.

  • CR3BP implemented as the primary supported dynamical model, with documented extension points.

Core Capabilities

  • Working implementations for generating at least one periodic orbit family.

  • Working implementations for generating at least one quasi-periodic orbit or torus.

  • Working implementations for computing and propagating stable and/or unstable manifolds.

  • Support for at least one class of resonant orbit with continuation.

  • Deterministic and reproducible workflows for all implemented capabilities.

Data Generation and Export

  • Ability to generate and propagate large ensembles of trajectories programmatically.

  • Data export functionality suitable for downstream machine learning workflows.

  • A curated set of default initial conditions and example orbit families committed to the repository.

Visualization and Analysis

  • Built-in visualization utilities for orbits and invariant structures.

  • Ability to generate at least one publication-quality figure or animation directly from the codebase.

  • Clear separation between numerical computation and visualization logic.

Documentation and Onboarding

  • A "getting started" guide that allows a new student to run a basic example end-to-end.

  • At least one tutorial covering a complete workflow (e.g., orbit generation → manifold propagation → visualization).

  • High-level design documentation describing architectural choices and extension points.

Software Quality and Sustainability

  • Unit tests covering core numerical routines and interfaces.

  • Continuous integration configured to run tests automatically.

  • Coding standards and contribution guidelines documented in the repository.

Collaboration and Process

  • Regular biweekly program meetings held and documented.

  • Active use of issues and pull requests for substantive work.

  • Evidence that multiple program members are using the shared tools in their own research.

Faculty Review and Oversight

  • One structured code and design review conducted with the PI.

  • A short summary document or presentation capturing current capabilities, limitations, and next steps.

Undergraduate Integration

  • At least one undergraduate successfully using the tools for analysis or experimentation.

  • Undergraduate-facing scripts, notebooks, or documentation that require minimal setup.