The code used in this tutorial is available!
Code can be found at industrial_training repository in gh_pages folder. Use kinetic branch.
There are two options for utilizing the ROS-Industrial training materials. The first recommended option is to utilize a pre-configured virtual machine. The second option is to install a native Ubuntu machine with the required software. The virtual machine approach is by far the easiest option and ensures the fewest build errors during training but is limited in its ability to connect to certain hardware, particularly over USB (i.e. kinect-like devices). For the perception training a .bag file is provided so that USB connection is not required for this training course.
Virtual Machine Configuration (Recommended)¶
The VM method is the most convenient method of utilizing the training materials:
Start virtual machine
Log into virtual machine, user:
rosindustrial(no spaces or hyphens)
Get the latest changes (Open Terminal).
cd ~/industrial_training git checkout kinetic-devel git pull ./.check_training_config.bash
Limitations of Virtual Box¶
The Virtual Box is limited both in hardware capability(due to VM limitations) and package installs (to save space). Kinect-based demos aren't possible due to USB limitations.
Common VM Issues¶
On most new systems, Virtual Box and VMs work out of the box. The following is a list of issues others have encountered and solutions:
- Virtualization must be enabled - Older systems do not have virtualization enabled (by default). Virtualization must be enabled in the BIOS. See http://www.sysprobs.com/disable-enable-virtualization-technology-bios for more information.
PC Configuration (NOT Recommended)¶
An installation shell script is provided to run in Ubuntu Linux 16.04 (Xenial Xerus) LTS. This script loads all the programs needed and configures the environment.
The following is a quick check to ensure that the appropriate packages have been installed and the the
industrial_training git repository is current. Enter the following into the terminal:
Open Source Feedback
See something that needs improvement? Please open a pull request on this GitHub page