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Built for roboticists

Robot middleware that just works.

No serialization on the local hot path. No QoS micromanagement. No surprises. Just typed messages over shared memory at the latency of a function call. Try the Quickstart

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What Cerulion is

Cerulion is a Rust middleware for robotics and real-time systems. You compose your application as a graph of nodes that pass messages over zero-copy shared memory, and you build, wire, and run the whole thing through one CLI: cerulion. It gives you the latency of raw shared memory with the ergonomics of a typed, macro-driven node API, plus a simulated clock that makes runs deterministic and replayable. It’s the foundation of a modern robotics stack — built to be the faster, more deterministic successor to ROS 2.
A Cerulion graph of nodes exchanging messages over shared memory
Cerulion is in closed alpha — early access for teams who want a faster, more deterministic robotics stack ahead of the public release. Everything documented here — the CLI, node macro, and graph/schema formats — is real and verified against the current build. Access is curated today; request an invite to start building.

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Why teams use it

Zero-copy pub/sub

Nodes exchange messages over iceoryx2 shared memory. Reads and writes go straight to the payload, with no serialization on the local hot path.

Deterministic runs

Execution is driven by a simulated clock stepped in 1 ms increments, so the same graph and inputs produce the same ordering. That makes runs easy to debug and replay.

Trigger policies

Decide when each node fires (periodic, data-triggered, synchronized, or external) with per-node tick deadlines that warn loudly when missed.

Ergonomic node API

Define a node as a Rust struct with #[cerulion_node]. Field attributes declare ports; the macro rewrites self.<port> access into zero-copy shared-memory reads and writes for you.

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Start here

Installation

Set up the Rust toolchain, get the cerulion CLI, and verify it works.

Quickstart

Build and run a complete two-node graph, then watch its messages with topic echo.

Concepts

Learn the mental model: workspaces, nodes, graphs, topics, and schemas.