Shield AI and Sedaro team up to accelerate on-orbit autonomy
Washington, D.C. - Shield AI and Sedaro have formed a partnership to bring Shield AI's Hivemind Pilot autonomy software into Sedaro's space-systems simulation platform. The goal: develop, test, and demonstrate autonomous spacecraft behaviors in high-fidelity, space-relevant scenarios before pushing to orbit.
Hivemind - already proven on air and maritime systems - will use Sedaro's cloud-based environment as its primary development and test bed for orbital missions. This setup aims to shorten iteration cycles and reduce risk by validating multi-spacecraft behaviors at scale prior to deployment.
Why this matters for operations
Operations leaders are under pressure to field resilient, agile space capabilities without introducing avoidable risk. This pairing offers a clearer path from concept to on-orbit execution by merging autonomy development with realistic simulation and scenario stress-testing.
For program schedules, it means fewer late surprises. For readiness, it means you can rehearse complex behaviors and decision logic long before a vehicle reaches orbit.
What the stack enables
- Proximity operations: plan, test, and validate approach/retreat behaviors and safety thresholds.
- Swarm coordination: synchronize multi-satellite tasking and cooperative behaviors.
- Defensive counter-space: evaluate tactics for contested environments and degraded comms.
- Battle-management support across constellations: distribute sensing, decision-making, and tasking.
Ground vs. edge autonomy: operational choices
The partnership will explore deployment concepts from ground-controlled frameworks to onboard, edge-hosted autonomy. Ground-heavy control can simplify governance and updates but depends on reliable links and latency tolerance.
Edge autonomy cuts comms dependency and supports faster reaction cycles in dynamic scenarios. The trade: higher on-board compute, robust fault management, and tighter V&V requirements. Your architecture decision should reflect mission timelines, risk posture, and comms availability.
How to operationalize this (action checklist)
- Define clear CONOPS and guardrails: autonomy permissions, abort logic, collision risk thresholds, and comms-loss behaviors.
- Build a scenario library: nominal ops, degraded modes, edge cases, and contested spectrum events.
- Lock in V&V metrics early: decision latency, fault detection/isolation/recovery timing, link budgets, and handover success rates.
- Plan sim-to-flight parity: sensor models, timing, ephemeris accuracy, and actuator limits that mirror flight hardware.
- Harden update pathways: secure deployment of autonomy updates (ground and on-orbit) with rollback options.
- Schedule phased trials: lab-in-the-loop, HIL, limited on-orbit demos, then full operational rollout.
Risk, schedule, and coordination
High-fidelity simulation up front can compress test timelines and expose integration issues before launch. Expect fewer late-stage design pivots and more predictable on-orbit commissioning.
Cross-team coordination remains critical. Ensure ops, autonomy engineers, safety, and comms teams work from the same scenarios, thresholds, and success criteria to prevent drift between simulation and flight rules.
What to watch
- Demonstrations showing swarm behaviors and proximity operations validated in simulation, then replicated on orbit.
- Evidence of autonomous ops performance in limited or denied comms environments.
- Standardized V&V frameworks for on-orbit autonomy to streamline approvals and updates.
Learn more about the companies involved: Shield AI and Sedaro.
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