Getting started

To quickly get started with the Robot Learning Lab follow the steps below.

1. Register yourself

The first step is to register yourself. You can do this here. We support regular user registrations using your Email address or you can log in with a Google or Github account. If you are a student or employee at KIT, you can directly log in with your KIT account.

2. Running demos

To get familiar with the submission processing in the lab, you can test some of the demos. These are example implementations for projects that are currently hosted in the lab or that will become available at a later point. Once you submitted one or several demos, you can follow the processing of your jobs in the jobs list view. There you can view a live feed of the webcam while the job is running and inspect job data, including log files once the job has finished.

The job processing chapter explains how your submission is handled by the lab system and what the different job states mean.

3. Setup your development environment

Before you can write your own code and submit it, you need to set up your development environment. You can either do a manual installation of all required packages or start with our ready-to-use virtual machine image.

We recommend the manual installation if you already have an Ubuntu or Debian system on your machine or if you are interested in setting up an Ubuntu installation by yourself. Otherwise the VM image is easier to get started and it works on Windows and macOS.


Additonally to these installation options, a web-based development environment is currently in development and will be offered as an alternative once it is ready.

4. Configure your API access

To be able to submit your code to the RLL you need to retrieve the API access token, which is used to authenticate your submission. Complete the following steps within your development environment, i.e. if you are using the RLL VM follow these steps in the VM.

  1. Download your API access config from the settings page and save it to the config folder of the rll_tools package in your workspace. This should be the full path to the file:



    The leading ~ in the path refers to your users home folder, i.e. inside the VM the path resolves to: /home/rll/rll_ws/src/rll_sdk/rll_tools/config/api-access.yaml

    You only need to do this step once. The config contains an access token that you can use for an arbitrary number of submissions.

  2. Now you can make a submission by running:

    roslaunch rll_robot_playground_project submit_project.launch

    This command will create an archive of your source code for the Robot Playground project and upload it to the Robot Learning Lab API. If you did not yet make any changes to the source code, then it will simply upload the default hello world program. You can then follow the job in your jobs view.

    You can execute this command anytime you want to see your current code version running on one of the robots in the lab.

5. Writing your own code

If you successfully completed the steps above you are ready to write your own code for the Robot Learning Lab!

To get started you read up on the Development workflow. To get familiar with the development environment and the different ways to control the robot refer to the Robot Playground project, which is the starter project that lets you move the robot around using different commands. Or get an overview of the available movement commands first by reading the RLL MoveClient documentation.