Course of Product
Mastering with ROS:
Learn how to work with a TIAGo robot from PAL Robotics
TIAGo is a service robot designed to work in indoor
environments. TIAGo’s features make it the ideal platform for research, especially on ambient assisted living or light
industry. It combines mobility, perception, manipulation, and human-robot interaction capabilities for one specific goal: to be able to assist in research.
In this course, you are going to learn how you can start working with the TIAGo robot, explore its functionalities, and how to build some interesting ROS applications for it.
What you’ll learn
- Control of TIAGos joints.
- Navigation with TIAGo.
- Motion Planning with MoveIt!
- Perception with OpenCV
- Perception with PCL
Basic ROS, Basic Python, Basic Linux, Basic TF
Unit 1: Introduction to the Course
This Unit is an introduction to the TIAGo robot Micro Course. You’ll have a quick preview of the contents you are going to cover during the course, and you will also view a practical demo.
Unit 2: Control
In this Unit, you are going to see some basic information and tools that will allow you to control the TIAGo robot: move it around, move its joints… and even some interesting features that TIAGo provides!
Unit 3: Autonomous Navigation with TIAGo
The first thing you will need for a robot that patrols are the ability to move around without crashing into everything, right?. Well, that’s what you are going to learn in this Unit! For this you will learn:
- How to create a map of an environment
- Localize the robot within the map
- Path Planning with Obstacle Avoidance
- Send a sequence of waypoints and execute those movements
Unit 4: Motion Planning with MoveIt (Part 1)
In the following Unit you are going to check the different way of performing Motion Planning with TIAGo using MoveIt:
- Planning in joint space
- Planning in cartesian space
Unit 5: Motion Planning with MoveIt (Part 2)
Use Octomap in MoveIt! to compute the collision checking with the environment around the robot during the motion planning of poses given in cartesian space.
Unit 6: Motion Planning with MoveIt (Part 3)
Tabletop pick & place demo using monocular model-based object reconstruction based on ArUco markers and the pick and place pipeline in MoveIt!
Unit 7: Perception with OpenCV
Perform various Perception tasks using the OpenCV library.
Unit 8: Perception with PCL
Perform various Perception tasks using the PCL library.
In this MicroProject you will have to apply all you have learned during the COurse in order to create a program that makes TIAGo patrol around an environment.
Ready to get started?
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