Automation Workflow for De-Orbit and End-of-Life Maneuver Planning

Manual disposal planning is a high-stakes operational bottleneck, exposing operators to regulatory fines, denied future licenses, and the permanent loss of valuable orbital slots. Automating this workflow directly protects revenue and licensing authority by ensuring compliant, fuel-optimal de-orbit or graveyard maneuvers. The custom architecture must ingest long-term solar and atmospheric drag forecasts, propagate orbits under uncertainty, and integrate with mission planning systems like AGI's STK or internal flight dynamics software to reserve fuel and schedule critical ground station passes for command uploads.

Implementation requires a multi-agent system, often built on LangGraph or a custom orchestrator, to sequence propagations, optimize under constraints, and handle exceptions like insufficient fuel. Controls are critical: human-in-the-loop approval gates for final maneuver authorization, continuous monitoring against the updated debris catalog post-maneuver, and immutable audit trails for regulators like the FCC or NOAA. The result is a defensible, automated operating procedure that turns a compliance risk into a managed, repeatable process, securing the operator's long-term orbital assets.

This workflow automates the high-stakes operational bottleneck of planning a satellite's controlled re-entry or graveyard orbit maneuver years in advance. The business imperative is clear: avoid seven-figure regulatory penalties for non-compliance and protect the long-term economic value of licensed orbital slots. Savings come from eliminating manual long-term trajectory modeling under solar and atmospheric drag uncertainty, and from optimizing the remaining propellant budget to extend the satellite's revenue-generating mission life before the final disposal burn.

Implementation integrates a high-fidelity propagator agent with fuel-optimization logic, connecting via API to mission planning systems like AGI's STK or internal flight dynamics software. The architecture requires strict controls: human-in-the-loop approval gates before command upload, continuous monitoring of subsystem health for execution readiness, and immutable audit trails for regulator and insurer reporting. Rollout is sequenced, starting with non-critical assets, to validate the autonomous planning logic against ground-truth simulations before full fleet deployment.

Phase 1 establishes the foundational data pipeline and deterministic propagator, ingesting TLEs and operator ephemerides into a cloud-based orchestrator like LangGraph. This initial build focuses on creating a reliable 25-year trajectory forecast under solar and atmospheric drag uncertainty, validating against historical disposal events. The deliverable is a dashboard showing each asset's projected decay timeline and compliance status, providing immediate visibility into portfolio risk and the baseline for fuel reservation logic without any autonomous action.

Phase 2 integrates the fuel-aware planning agent and the Mission Planning System (MPS), such as AGI's STK or an internal scheduler. The agent evaluates disposal windows against reserved fuel, ground station passes, and operational constraints to generate candidate maneuver sequences. In Phase 3, we implement human-in-the-loop approval gates within the operator's existing change management workflow and add comprehensive observability for audit trails. This staged approach de-risks the build, allows for calibration of propagation models, and proves the fuel-saving logic before full fleet deployment.

This workflow automates the high-stakes planning of disposal maneuvers to comply with the 25-year rule and specific orbit regulations, directly protecting against regulatory penalties and preserving future orbital slot access. The operational bottleneck is the manual, months-ahead analysis required to model long-term orbit decay under solar and atmospheric drag uncertainty. Savings come from optimized fuel expenditure, extended mission life, and the elimination of manual compliance reporting. The architecture integrates high-fidelity propagators (e.g., Orekit, GMAT) with mission planning systems like AGI's STK and satellite telemetry to reserve fuel and schedule ground passes.

Implementation requires a phased rollout, starting with a shadow mode that simulates maneuvers against the operational catalog without command generation. The first live phase would handle low-risk, well-characterized assets, with mandatory human approval for all command uploads. Full automation for pre-approved scenarios would follow, contingent on proven model accuracy and robust exception routing to ground controllers. Critical controls include pre-maneuver 'what-if' simulations against the latest debris catalog, cryptographic signing of command sequences, and immutable audit logs linking every decision to its regulatory rationale for insurers and agencies like the FCC or UNOOSA.

This workflow automates the high-stakes, multi-year planning of disposal maneuvers to meet regulatory deadlines and avoid financial penalties. It eliminates the manual, error-prone process of long-term orbit propagation under solar and atmospheric drag uncertainty. The business value is direct: it protects the operator's license to operate, preserves the economic value of the orbital slot for future assets, and prevents the satellite from becoming a liability that generates costly debris or regulatory fines. Implementation requires integrating with high-fidelity propagators, mission planning systems, and fuel telemetry.

The architecture centers on an orchestrator agent that triggers planning cycles based on regulatory timelines and remaining fuel. It ingests current ephemeris and telemetry, then runs Monte Carlo simulations through a high-fidelity propagator (e.g., Orekit, GMAT) to model decay under solar flux and drag uncertainty. An optimizer agent calculates the fuel-minimal burn sequence, reserving margin for contingency. The resulting plan is routed through a human review gate in the mission control system before command sequence generation and integration with the ground station schedule for upload. Critical controls include pre- and post-burn trajectory validation, immutable audit logging for regulators, and exception routing for plan deviations.