Autonomous Go/No-Go Decision Workflow for Last-Ditch Maneuvers

When a conjunction is imminent and ground communication latency precludes human review, a custom autonomous decision workflow must execute. This system automates the final go/no-go authorization for an avoidance burn by evaluating real-time risk probability, satellite health telemetry, fuel reserves, and maneuver feasibility against a pre-approved policy framework. The operational upside is the elimination of catastrophic collision risk for high-value assets, protecting billions in capital and preserving orbital slots. Implementation requires integrating with onboard flight software, propulsion systems, and ground-based SSA data feeds via secure, low-latency links.

The architecture hinges on a multi-layered agent built with frameworks like LangGraph for deterministic orchestration, incorporating hard-coded safety rules (e.g., minimum fuel reserves) alongside ML models for covariance-realistic risk scoring. Controls include cryptographic approval of the decision logic, a mandatory pre-burn validation against a digital twin simulation, and immutable logging of all inputs and the agent's rationale for the audit trail. Post-maneuver, the workflow automatically updates operator dashboards, files reports with systems like CARA, and triggers mission re-planning agents to recover lost operational time, ensuring the loop is closed with full operational accountability.

This workflow automates the highest-stakes decision in satellite operations: authorizing a final avoidance burn when a conjunction is imminent. It eliminates the fatal delay of human-in-the-loop review, directly protecting multi-million dollar assets from catastrophic loss. The operational upside comes from a deterministic, rules-based core evaluating final risk probability, satellite health telemetry, and precise fuel reserves, overlaid with an ML agent for anomaly detection in sensor data. Savings are measured in avoided total loss, not just labor minutes.

Implementation integrates with the satellite's flight software and ground systems like AGI's STK or NASA's GMAT for high-fidelity propagation. The agent is deployed as a containerized microservice within the operator's secure ops network, with direct APIs to telemetry databases and command systems. Controls include pre-flight simulation of the decision logic against historical scenarios, a mandatory cryptographic approval from a separate watchdog agent, and continuous monitoring of the agent's own performance drift. Post-event, the system auto-generates a comprehensive report for regulators and insurers, detailing every input, gate outcome, and the executed command sequence.

This workflow automates the final, time-critical decision to execute an avoidance maneuver when a high-risk conjunction is detected within a response window shorter than human reaction loops. It eliminates the operational bottleneck of convening an emergency review board, compressing a multi-hour process into seconds. The business value is unambiguous: preventing a catastrophic collision that could result in total asset loss, massive liability, and the generation of persistent debris. Savings come from preserving a multi-million dollar satellite and avoiding regulatory penalties, while the upside is maintaining mission continuity and protecting orbital slots.

Implementation requires integrating the decision agent with the conjunction data pipeline, satellite telemetry system (e.g., via TMF or custom APIs), and the flight dynamics subsystem. The agent itself is built using a framework like LangGraph to orchestrate specialized modules for probability scoring, fuel modeling, and constraint checking. Critical controls include explainability layers that record the decision rationale, immutable audit trails for regulators and insurers, and configurable human-in-the-loop escalation gates for edge cases. Deployment is typically hybrid, with the scoring logic hosted in a low-latency cloud or ground segment, while the final command authorization may integrate with legacy mission control systems like COTS software or custom operations platforms.

This workflow automates the terminal decision to execute an avoidance maneuver when a high-confidence conjunction is imminent—typically within hours. It eliminates the latency of human-in-the-loop review, which can be the difference between a collision and a near-miss. The business value is direct: protecting multi-million dollar assets from catastrophic loss and avoiding liability for generating new debris. The system ingests final conjunction data messages (CDMs), real-time satellite telemetry for fuel and subsystem health, and mission priority flags to evaluate the go/no-go condition under pre-defined operational rules.

Implementation requires tight integration with the flight dynamics system for ephemeris validation, the satellite command and control for telemetry, and a high-integrity messaging layer. The orchestrator, built on frameworks like LangGraph, executes a deterministic decision tree augmented by ML models for covariance realism assessment. Critical controls include a pre-flight simulation of the authorized burn against the full catalog, a mandatory cryptographic sign-off from a ground-based security module, and immutable logging of all inputs and the decision rationale for post-event review by insurers and regulators like the FCC.