Astral sits at the intersection of geospatial science, cryptography, and trusted computing. We publish our research openly and welcome academic collaboration.
Our foundational paper on composable location proofs — how to combine evidence from multiple proof-of-location systems into credible, verifiable claims about physical presence.Read on Flashbots Collective
How do you combine evidence from independent proof-of-location systems (device attestation, network triangulation, institutional records) into a structured credibility assessment? Our location proofs framework approaches this by defining claims, stamps, and multi-factor verification. The exact structure of the resulting credibility vector — its dimensions and how they’re computed — is itself an open research question.
How do you prove that a spatial computation (distance, containment, intersection) was performed correctly on specific inputs? Today we use TEE execution with signed results. Future work explores zero-knowledge proofs for spatial predicates.
As autonomous agents (drones, vehicles, robots) operate in physical space, how do you create verifiable records of where they were and what spatial constraints they respected? This connects geofence compliance, corridor verification, and auditable spatial logs.
Astral’s core infrastructure is developed in the open, and more is being opened as the Research Preview matures. Contributions, issues, and research collaborations are welcome.GitHub
If you’re working on related problems — verifiable computation, location privacy, spatial data integrity, or autonomous systems accountability — we’d like to hear from you. Open an issue on GitHub or reach out through the channels listed there.
