RobotsGov — runtime governance for robots that think
Most "robot safety" stops at the body: collision avoidance, e-stops, functional safety. That's necessary, but it doesn't answer a different question — will the AI inside the robot do something it was never authorized to do?
RobotsGov is a control plane that decides what a robot is allowed to do and enforces it before the action executes — not a dashboard of what already happened. Safety, compliance, and intent gated at runtime, across industrial fleets and domestic robots.
How it works
A governed control topic sits in front of the robot's native command interface. Every verb the AI emits is evaluated against tenant policy before it reaches the hardware:
Allow — in-scope commands pass through unchanged
Block — out-of-policy verbs are denied at the gate; they never become commands on the wire
Mask / HITL — sensitive actions are minimized or held for human approval
Each decision is written to a tamper-evident signed ledger (Ed25519, hash-chained). p99 enforcement latency is 0.825 ms — below the noise floor of the robot's own control loop.
Proven end-to-end on real humanoid SDKs
This isn't a mock. We took a publicly available humanoid SDK and put our governance bridge in front of it. The governed topic translates each verb to the robot's native protocol (DDS → LCM), and we verified on the wire that forbidden verbs (e.g. high-risk locomotion, fall-to-ground) never became commands — while authorized ones passed through governed and logged. Same model that governs cloud agents, now governing a physical robot.
Open at the base
RobotsGov runs on two open protocols, published with permanent DOIs under Apache-2.0:
AIRGP — Artificial Intelligence Runtime Governance Protocol (DOI 10.5281/zenodo.20001903)
A2ASTC — Agent to Agent Software Team Compliance (DOI 10.5281/zenodo.20002917)
The standard is open and auditable — governance shouldn't be locked to a single vendor.
One governance model, from cloud to robotics.
https://robotsgov.com