TODO: add information that is useful for instructors
The LX recipe contains components of the exercise that the student should not need to change and are effectively hidden from view. There are a few files here that will require some attention in the creation of the learning experience
Specify any apt or python dependencies needed in the
dependencies-apt.txt and
dependencies-py3.txt respectively.
You need to specify a BASE_IMAGE in the Dockerfile. This
choice defines what is already in the docker image and can be used in the
running of the exercise.
Reasonable choices could be:
dt-commons: likely a good choice if the LX is pure python and doesn't require ROS.dt-ros-commons: likely a good choice if you would like to use ROS in a standalone fashion (i.e., your exercise includes all the nodes that are needed)dt-core: a good choice if you would like to use one or more of the nodes defined in the packages in thedt-corerepository.
Coming soon:
- ROS2 base image
- Machine learning base image
By default, each LX is compatible with the Duckiematrix.
See the README in the LX template
for more details on how to deploy this capability through the dts code API.
You can define the exact configuration of the Duckiematrix environment in the
assets/duckiematrix directory. For more details see
the Duckiematrix manual.
It is also possible to customize the noVNC desktop. TODO: add details.