ARI Tutorials

These tutorials have been created to learn how to use ARI, the mobile manipulator by PAL Robotics, in the Gazebo simulation environment running on an Ubuntu computer.

Tutorials Installation

  1. Installing Ubuntu with ROS

    This tutorial describes the steps needed to get a proper Ubuntu and ROS installation to have a system up and running for the ARI tutorials.

  2. Installing ARI Simulation

    A brief summary of commands to install the required packages for ARI simulation



  1. Teleoperating the mobile base with the keyboard

    How to move ARI using the key_teleop package.

  2. Moving the base through velocity commands

    This tutorial shows how to move the base by sending velocity commands to the appropriate topic.

  3. Joint Trajectory Controller

    Example of how to move ARI's arm using a joint trajectory action.

  4. Moving individual joints

    Different ways to move individual joints of ARI are explained.

  5. Head control

    Example on how to move ARI's head using an action that makes the robot look to a given direction.

  6. Playing pre-defined upper body motions

    Tutorial on how to play back pre-defined upper body motions with ARI using the play_motion package.


Autonomous navigation

  1. Create a map with slam_toolbox

    This tutorial shows how to create a map of the environment using the ARI's torso RGB-D camera.

  2. Localization and path planning

    Learn how to run laser-based localization and autonomous navigation avoiding obstacles by means of global and local path planning.




    1. Corner Detection (C++)

      There are two corner detector algorithms often used in the OpenCV library, the Shi-Tomasi and Harris functions. In this simple tutorial you will see how changing two parameters can affect the corner detection

    2. ArUco marker detection (C++)

      This tutorial shows how to detect fiducial markers using the ArUco library and to get its 3D pose.

    3. Person detection (C++)

      ROS node using the OpenCV person detector based on HOG Adaboost cascade

    4. Face detection (C++)

      Example of ROS node embedding OpenCV's face detector.

    5. Planar object detection and pose estimation (C++)

      Planar textured object detection based on feature matching between live video feed an a reference image of the object. Then, the pose of the object is determined by homography estimation and provided the size of the object.


Interacting with humans

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Wiki: Robots/ARI/Tutorials (last edited 2023-07-26 09:58:11 by PALmarketing)