ROBOT GRAPH DEFINITION

A machine-readablestandard for cognitive embodiment.

OpenRGD gives AI systems a structured way to understand a robot body, its operational limits, capabilities, lifecycle and relationships with other agents.

OPEN STANDARDMACHINE READABLENON-ACTUATING BY DESIGN
openrgd.graph / domains INTERACTIVE
01

Foundation

stable

Physical body and hardware reality: structure, joints, inertials, actuation evidence and source provenance.

01description
02actuation
03sensors
04hardware
semantic domain01_foundation
Standard bundle0.2.0DRAFT
Python toolchain0.1.1ALPHA
Agent contracts0.1.0CANDIDATE

WHY OPENRGD

The missing semantic layer between AI and robots.

Robot description formats are excellent at describing geometry, joints and simulation state. AI systems need more: explicit capability, operational boundaries, provenance and lifecycle context.

01

Beyond geometry

Describe what a body is, what it can do, what constrains it and where that knowledge came from.

02

Grounded AI context

Compile robot knowledge into deterministic, machine-readable context without silently authorizing physical execution.

03

Interoperability boundary

Keep semantic description, middleware export and embodied runtime responsibilities explicit and independently verifiable.

CANONICAL DOMAIN MODEL

One robot. Seven semantic domains.

Each domain carries its own authority and maturity instead of hiding assumptions inside one monolithic robot description.

00

Core

Coordination, manifests and kernel metadata.

foundation
01

Foundation

Physical body, hardware reality and structural evidence.

stable
02

Operation

Runtime constraints, safety and physiological operation.

stable
03

Agency

Capabilities, world model and action interfaces.

experimental
04

Volition

Values, alignment and decision governance.

experimental
05

Evolution

Lifecycle, wear, adaptation and continuity.

proposal
06

Ether

Collective, social and inter-agent protocols.

proposal

TECHNOLOGY CONTEXT

OpenRGD sits inside a larger embodied systems stack.

These concepts explain why a machine-readable embodiment layer matters and where OpenRGD stops.

DESCRIPTION FORMATS

One robot can exist across several description layers.

URDF, USD, SDF, MJCF and RGD overlap on physical facts, but each has a different center of responsibility.

SHARED KNOWLEDGE LAYER

Canonical facts. Independent OpenRGD context.

OpenRGD.org reads shared canonical entities from the multi-site knowledge layer, while its summaries, SEO and editorial framing remain specific to OpenRGD.

openrgd / terminal● ● ●
$ rgd init Robot
$ cd Robot

$ rgd import robot.urdf --out partial-robot
✓ foundation evidence extracted

$ rgd hash
OPENRGD_SOURCE_TREE_SHA256_V1
9d0f…a71c

$ rgd check --output json
{ "integrity": "verified" }

$ rgd boot --output json
{ "execution_authorized": false }

EVIDENCE → CONTEXT

Import what the source proves. Invent nothing.

OpenRGD can extract source-supported body evidence from URDF and USDA, preserve provenance and compile a deterministic non-actuating grounding context.

01URDF / USD
02IMPORT
03RGD GRAPH
04VERIFY
05COMPILE

RUNTIME BOUNDARY

Semantic intelligence stops before physical authority begins.

OpenRGD deliberately separates cognitive proposals from actuation. Runtime safety and body control remain explicit downstream responsibilities.

01CognitionProposalCOGNITION
02ActionIntent
03Somatic Translator
04CapabilityPlan
05Operation Safety Gate
06DecisionTrace
07Body Adapter
08HardwarePHYSICAL

OPEN ECOSYSTEM

Built to connect, not to replace everything.

OpenRGD is a semantic standard and toolchain root. It can coexist with robot description formats, middleware and physical runtimes.

01

Robot descriptions

URDF and supported OpenUSD evidence can enter the graph without losing provenance.

02

Static exports

Deterministic outputs can target middleware configuration without crossing the actuation boundary.

03

Contracts

Cross-component interfaces expose maturity, provenance and explicit responsibility.

04

Shared knowledge

Canonical robot facts can be reused across documentation, research and ecosystem tooling.

OPEN SOURCE · MIT LICENSE

Inspect the standard. Challenge the assumptions. Build on the graph.