AWS RoboMaker

Name: AWS RoboMaker API
Brand: AWS RoboMaker
Availability: InStock

★ Only Publicly Available OpenAPI DocumentDeveloper ToolsCi Cdhmac57 EndpointsREST

For Agents

Run ROS simulation jobs, generate synthetic worlds, and deploy robotics applications to device fleets in the cloud.

Connect the AWS RoboMaker to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the AWS RoboMaker, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Install Jentic One Beta (Self-Hosted)

Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with AWS RoboMaker API.

Launch and cancel ROS-based simulation jobs against custom robot and simulation applications

Run batched simulation jobs to parallelise scenario testing with CreateSimulationJobBatch and CancelSimulationJobBatch

Generate synthetic worlds and export them to S3 with CreateWorldGenerationJob and CreateWorldExportJob

GET STARTED

Start building with AWS RoboMaker API

Explore with Jentic

View OpenAPI Document

Jentic publishes the only available OpenAPI document for AWS RoboMaker, keeping it validated and agent-ready.

Jentic publishes the only available OpenAPI specification for AWS RoboMaker, keeping it validated and agent-ready. AWS RoboMaker is a managed service for building, simulating, and deploying robotics applications at scale. It runs ROS-based simulation jobs in the cloud, generates synthetic worlds for training, manages over-the-air deployment of robot software to fleets, and tracks simulation batches so engineering teams can iterate on perception and navigation models without standing up their own GPU infrastructure.

Use Cases

Patterns agents use AWS RoboMaker API for, with concrete tasks.

★ Cloud-scale robot simulation testing

Robotics teams use AWS RoboMaker to run ROS simulation jobs in parallel against new perception and navigation code without provisioning local GPU clusters. CreateSimulationJob spins up a Gazebo or other simulator with the team's robot application and a chosen world; CreateSimulationJobBatch fans the same scenario across many parameter variations so regression tests finish in minutes, not hours.

Call CreateSimulationJobBatch with 30 simulation requests covering varied lighting and obstacle layouts for the same robot application, then poll DescribeSimulationJobBatch until all complete.

Synthetic world generation for ML training

Perception teams use CreateWorldGenerationJob to produce thousands of procedurally varied indoor environments, then export them with CreateWorldExportJob to S3 for downstream training of object-detection and SLAM models. RoboMaker handles the variation parameters and storage, freeing engineers from running their own world-generation pipeline.

Submit CreateWorldGenerationJob with a worldCount of 500 against a residential template, then call CreateWorldExportJob to push the resulting worlds to s3://my-training-data/worlds/.

Over-the-air robot fleet deployment

Operations teams use the deployment APIs to push new robot software versions to fleets in production. CreateDeploymentJob targets a fleet, applies a deployment configuration, and tracks per-robot rollout status, so a release engineer can confirm the version is live on every device without writing custom orchestration. RegisterRobot and DeregisterRobot keep the fleet inventory current.

Call CreateDeploymentJob targeting fleet arn:aws:robomaker:::fleet/prod-warehouse with a new robot application version, then poll DescribeDeploymentJob until all robots report SUCCEEDED.

Agent-driven simulation workflow through Jentic

AI agents that orchestrate end-to-end robot release pipelines use Jentic to call CreateSimulationJob, DescribeSimulationJob, and CreateDeploymentJob without holding raw AWS credentials. Jentic stores the agent's keys in the MAXsystem vault, signs each request with SigV4, and returns the structured response so the agent can branch on simulation outcome before triggering deployment.

Search Jentic for 'launch a RoboMaker simulation job', load CreateSimulationJob, execute against the navigation_test simulation application, and on SUCCEEDED status trigger CreateDeploymentJob to the staging fleet.

Key Endpoints

57 endpoints — jentic publishes the only available openapi specification for aws robomaker, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/createSimulationJob

Launch a ROS simulation job

POST

/createSimulationJobBatch

Launch a batch of simulation jobs

POST

/cancelSimulationJob

Cancel a running simulation job

POST

/createWorldGenerationJob

Generate synthetic worlds for training and simulation

POST

/createWorldExportJob

Export generated worlds to S3

POST

/createDeploymentJob

Deploy a robot application version to a fleet

POST

/createFleet

Create a fleet for grouping robots

POST

/createRobot

POST

/createSimulationJob

Launch a ROS simulation job

POST

/createSimulationJobBatch

Launch a batch of simulation jobs

POST

/cancelSimulationJob

Cancel a running simulation job

POST

/createWorldGenerationJob

Generate synthetic worlds for training and simulation

POST

/createWorldExportJob

Export generated worlds to S3

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

AWS credentials are stored encrypted in the Jentic vault (MAXsystem). Each RoboMaker call is signed with SigV4 server-side and the agent only receives scoped, short-lived authorisation — raw access keys never enter the agent's context.

Intent-based discovery

Agents search by intent (e.g., 'launch a RoboMaker simulation job') and Jentic returns matching RoboMaker operations with their input schemas, so the agent calls CreateSimulationJob or CreateDeploymentJob without browsing AWS docs.

Time to first call

Direct RoboMaker integration: 2-4 days for SigV4 signing, IAM role plumbing, and simulation-application packaging. Through Jentic: under an hour for the API surface — search, load schema, execute (the simulation-application bundle still needs to exist in S3).

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

Amazon SageMaker

Train ML models on the synthetic data RoboMaker generates

Use SageMaker to train perception models on data exported from RoboMaker world-generation jobs; the two services connect through S3.

Complementary

AWS IoT SiteWise

Ingest telemetry from deployed robots once they are operating in the field

Use IoT SiteWise when you need to collect and model time-series data from robots after RoboMaker has deployed software to them.

Alternative

AWS IoT Greengrass

Edge runtime and fleet deployment for general IoT — more general than RoboMaker's robot-specific deployment

Choose Greengrass for general edge-device fleet management; choose RoboMaker when ROS-specific simulation and deployment workflows are required.

FAQs

Specific to using AWS RoboMaker API through Jentic.

Why is there no official OpenAPI spec for AWS RoboMaker?

AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call AWS RoboMaker via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the AWS RoboMaker API use?

AWS RoboMaker uses AWS Signature Version 4 HMAC signing with an access key ID and secret access key, optionally with a session token. Through Jentic, those credentials live in the MAXsystem vault and the agent never handles raw secrets — Jentic signs each request server-side.

Can I run my own custom simulator with AWS RoboMaker, or only Gazebo?

RoboMaker accepts a SimulationApplication that you build and upload (typically a containerised ROS + simulator bundle), so you are not restricted to Gazebo. The simulation application is registered via CreateSimulationApplication and referenced from CreateSimulationJob — but note AWS announced RoboMaker is on a deprecation path, so check current service status before adopting it for new workloads.

What are the rate limits for the AWS RoboMaker API?

AWS does not publish a fixed RPS in the spec; standard AWS API throttling applies. Long-running operations such as CreateSimulationJob also have concurrency limits per account and region — overage returns LimitExceededException, so production agents should poll capacity and queue jobs accordingly.

How do I launch a simulation job with the AWS RoboMaker API through Jentic?

Search Jentic for 'launch a RoboMaker simulation job', load the CreateSimulationJob operation schema, and call POST /createSimulationJob with your robotApplications, simulationApplications, and IAM role ARN. Then poll DescribeSimulationJob until status reaches Completed. Install the SDK first with pip install jentic.

Can the AWS RoboMaker API train ML models, or only run simulations?

RoboMaker itself runs simulations and generates synthetic worlds — it does not train models. The typical pipeline is: generate worlds with CreateWorldGenerationJob, export to S3 with CreateWorldExportJob, then train with Amazon SageMaker on that data. RoboMaker is the simulation and data-generation layer, not the training layer.