The tutorial is taking place in the Grand Ballroom, starting at 8.30 sharp!.
TRS 2014: Motivation
This tutorial is organized around a cross-platform robot development and simulation environment that can be installed in five minutes and that allows students to write control, navigation, vision or manipulation algorithms in a hundred lines of Matlab or Python code. The tutorial relies on the V-REP robot simulator, and on the Matlab Robotics Toolbox (RTB). The key feature of this combination is its ease of use – both tools are trivial to install. The tutorial is intended for teachers and students. Students will install the simulation environment on their laptop and learn everything they need to know to start implementing and testing robot algorithms. Teachers will return home with a ready-to-use recipe for organizing a master-level robotics project.
Because working with hardware is time-consuming, many Master-level and PhD-level robotics courses leave hardware issues aside, to give the students time to study theoretical concepts and information-processing algorithms. Unfortunately, hardware-free courses often come with no hands-on exercises, which impedes learning. This tutorial discusses one solution to this problem: allowing students to gain practical experience in a simulated environment. Open-source simulators have existed for a long time, but their limited ease-of-use made them impractical for teaching. Ease of use is crucial in teaching: The software must be robust, multi-platform, and its installation has to be trivial. V-REP, the simulator on which this tutorial is based, can be installed on Linux, OSX and Windows simply by uncompressing zip archive.
Software development is another major challenge in robot development. This tutorial is based on the Robotics Toolbox for MATLAB (RTB), a library of robot-oriented software building blocks. Its Matlab implementation makes it accessible to branches of engineering where fluency in C++ is not expected.
The aim of this tutorial is to present an environment, based on V-REP and RTB, that allows students to control a robot from Matlab. The environment consists of a set of Matlab scripts, and a V-REP file modeling a mobile robot and a building floor. Running a single Matlab command establishes a connection between Matlab and V-REP. The user is then able to recover sensor data (images, scans, odometry), process those data, and send commands to the robot's actuators. The robot's sensors and actuators are accessed via Matlab functions:
vrep.simxSetJointTargetVelocity(id, wheel1, 10);
An understanding of the simulator itself is not required, as all the programming is done through the Matlab interface.
The tutorial will cover the V-REP Matlab API and RTB, and it will provide a recipe for organizing a Master-level robotics project. The project consists in using a mobile robot to pickup groceries from a table and move them to different baskets distributed across a house. The project involves control, navigation, mapping, vision and manipulation. The recipe is composed of a website that presents the project, a Matlab script that illustrates access the robot's sensors and actuators, and a Git repository containing the V-REP model and Matlab scripts discussed above. The website covers multiple aspects of the project, including its descriptions, install instructions, milestones paving the way for the students, and a description of the robot and its capabilities.
The tutorial is intended for both teachers and students. A part of the tutorial is reserved for helping students install the simulation environment on their laptop. The tutorial will hopefully help students realize the ease with which a simulator allows them to test ambitious ideas.
We will release the material presented above under an open license, allowing anyone to copy, improve, and hopefully contribute back, to provide robotics students with an excellent learning experience.
Call for Abstracts
We welcome the submission of abstracts (200 words) about one's experience in teaching or learning robotics with a simulator, or in doing research with a simulator. In particular, we will welcome presentations by students relating a project implemented with RTB or V-REP, and presentations by teachers relating their experience in teaching with a simulator. Selected authors will present their ideas to the participants during the tutorial.
|Submission deadline||August 15, 2014|
|Notification of acceptance||August 18, 2014|
Abstracts should be sent via email to Renaud Detry.
The tutorial will take place on the 14th of September, 2014. The (tentative) program of the day is as follows:
Session 1: 8:30–10:00 (1:30 hours)
- 8:30–8:40: Welcome and Introduction
- Renaud Detry (University of Liège, Belgium)
- 8:40–9:20: Tuto 1
- The V-REP Simulator and its Matlab API
Marc Freese (Coppelia Robotics)
- 9:20–10:00: Tuto 2
- The Robotics Toolbox for MATLAB
Peter Corke (Queensland University of Technology, Australia)
Session 2: 10:30–12:30 (2 hours)
- 10:30–11:10: Tuto 3
- A Robotics Project in Matlab
Renaud Detry (University of Liège, Belgium)
- 11:10–11:35: Practical Session
- Installation on the Participants' Computers
- 11:35–11:45: Selected Contributions
- KUKA LWR4 dynamic modeling in V-REP and remote control via Matlab/Simulink
Marco Cognetti and Massimo Cefalo (Sapienza Universita di Roma)
- 11:45–12:00: Discussion and Closing
If there is time, participants will have the opportunity to work on a small project based on the TRS framework. Follow the instructions available from the TRS setup page to install V-REP and get the TRS code. The template file for this lab are in the same Git repository as the rest of TRS, in a branch called trs2014-tutorial. To start working, switch to that branch:
[cd to the root of the TRS repository]
git checkout trs2014-tutorial
An alternative is to directly download a ZIP archive of the contents of that branch.
In the trs/youbot directory, you will find a script named control.m. Your task is to fill in the blanks in that script to make the robot follow the trajectory stored in the variable traj.
OrganizersRenaud Detry, University of Liege, Belgium
Peter Corke, Queensland University of Technology, Australia
Marc Freese, Coppelia Robotics