Welcome to the Hello GRID tutorial! This guide will walk you through setting up and running your first GRID session using the GRID Enterprise platform.
By default, all commands in this tutorial are executed on the local machine. If you are using a remote machine, you must specify it explicitly using the @<machine_name> syntax.
Before starting this tutorial, ensure that you have GRID Enterprise installed on your local machine. If you haven’t already installed GRID Enterprise, refer to the installation guide for detailed instructions. After installation, please make sure your ‘resource configuration’ file is set up correctly - you should have received this file during onboarding.
The first step is to log into the GRID platform and initialize the containers. Open your terminal and run the following command:
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grid
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.d8888b. 8888888b. 8888888 8888888b.d88P Y88b 888 Y88b 888 888 "Y88b888 888 888 888 888 888 888888 888 d88P 888 888 888888 88888 8888888P" 888 888 888888 888 888 T88b 888 888 888Y88b d88P 888 T88b 888 888 .d88P "Y8888P88 888 T88b 8888888 8888888P"General Robot Intelligence Development Platform - Enterprise versionDeveloped by General Robotics, Inc. (c) 2025Loading resource configuration from /home/grid/.grid/resource_config.json...Started container server on 0.0.0.0:8060Samples currently at /home/grid/.grid/samplesType 'help' or 'license' for more info.GRID #
You can sign in using the provided credentials. Login using the command login and then initialize the containers using init.
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GRID # loginLogging in to General Robotics - GRID registry...Login successful!GRID # initPlease choose the simulator you wish to use:1: airgen2: isaacEnter your choice: 1Starting GRID containers for airgen on local...Spinning up containers with profile airgen...WARN[0000] The "OPENAI_API_KEY" variable is not set. Defaulting to a blank string.[+] Running 3/3 ✔ Container grid_core Started0.5s ✔ Container grid_sim_airgen Started0.5s ✔ Container grid_server Started0.6sChecking container statuses...grid_core: ✓grid_server: ✓grid_sim_airgen: ✓Containers are active.Setting up assets... Done.
This command spins up the necessary containers on your local machine, preparing the environment for your session.
If the containers do not already exist, the images will be downloaded, and the containers will be started. Please note that this process may take a few minutes.
Let’s now start a session that runs a pre-configured simulation. Execute the following command in your terminal:
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session start hello_grid
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No session configuration was passed. Using a sample configuration from ~/.grid/sample_session_config_airgen.json...2025-02-11 23:33:59,542 - INFO - Initializing sessionDownloading assets...File already exists at destination. Skipping download.2025-02-11 23:33:59,774 - INFO - HTTP Request: POST http://127.0.0.1:8000/start_session "HTTP/1.1 200 OK"response: Initializing session...response: Downloading content..response_end: Session has been started successfullySession started successfully.2025-02-11 23:34:10,467 - INFO - Session started successfully.
This starts a session named hello_grid. Because we did not explicitly specify a session configuration, GRID will use a sample configuration file to start the session. As the console output shows, this configuration file resides at ~/.grid/sample_session_config_airgen.json.
To check all active sessions, use the following command:
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session list
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grid> session list2024-09-10 17:10:53,338 - INFO - HTTP Request: GET http://localhost:8000/is_idle?session_id=hello_grid "HTTP/1.1 200 OK"+--------------+-----------+----------------------------------+| Session ID | Node IP | Last Active Time |+==============+===========+==================================+| hello_grid | localhost | 2024-09-10T23:42:51.674976+00:00 |+--------------+-----------+----------------------------------+
Now that we have the session running, let’s create a notebook to interact with the simulation. To do this, go to the notebook interface and click on New in the top right to create a new notebook.
You can also use pre-trained AI models for computer vision, vision-language, SLAM, point tracking, and more. To use an AI model, you can import it and use it in your code. Let us try to use an object detection model to detect objects in the image captured by the robot.
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from grid.model.perception.detection.owlv2 import OWLv2det_model = OWLv2(use_local=True)det_model.run(image.data, "ball")
You’ve completed the Hello GRID tutorial. You’ve successfully logged in, started a session, opened a simulation, and cleaned up your environment. This is the beginning of what you can achieve with GRID Enterprise. Explore the advanced features like running sessions on remote machines, mounting custom storage, and integrating your own AI models.
Now that we have successfully set up the development environment, you can explore the AirGen, Isaac, and AI Models sections to dive deeper into the capabilities of the GRID Enterprise platform.