Robotics

Project related to the Robotics Course taught at Unicamp.

https://www.ic.unicamp.br/~esther/teaching/2019s2/mo651/index.html

Setup

Supports install direct on the system or on a docker container.

For a direct install, the setup is done in a folder isolated from the rest of the system (assumes a Linux 64 bits).

For a docker install, the setup is done in an Ubuntu 18.04 LTS image provisioned with the same scripts of direct install.

Development setup for VS Code is available in direct install.

Running V-REP in a Docker container is also supported in direct install.

Direct Install

install.sh

setup/install.sh

Jupyter:

bin/jupyter-lab
# hold the terminal
# Ctrl-C terminate Jupyter Lab.

Open http://localhost:8888/ in the web browser to access Jupyter Lab.

Running V-REP with Docker

[ README ]

In case the host system is not Ubuntu 18.04 or there are missing dependencies, it is possible to run V-REP on a Docker container provided at docker folder.

docker/vrep/build.sh
docker/vrep/run.sh

V-REP window opens as a normal GUI Application on Host.

Docker Install

[ README ]

Install:

docker/bundle/build.sh

Starting the container (runs Jupyter Lab):

docker/bundle/run.sh
# Return after the container is started

Terminating the container:

docker/bundle/shutdown.sh

Open http://localhost:8888/ in the web browser to access Jupyter Lab.

Development

Assuming direct install.

Update with VS Code settings and required Python packages.

setup-dev.sh

setup/setup-dev.sh

Content

bin

Commands to start applications:

bin/jupyter-lab: start Jupyter Lab server (workspace as work directory)
bin/julia-repl: start Julia REPL prompt (PROJECT_HOME as work directory)
bin/python-repl: start Python REPL prompt (PROJECT_HOME as work directory, using Jupyter Console running rebotics_python kernel)
bin/run-notebooks: execute and update each .ipynb from workspace non-interactively.

conf

Project configuration.

env.sh: define environment variables of the project.

workspace

Home of experimental code, drafts and examples, normally as Jupyter notebooks.

setup (README)

Scrips to automate initial installation of Conda, Python, Julia and V-REP on a Linux host.

docker (README)

Containerized project infrastructure (containers encapsulating application and dependencies).

Supports a robotics container with all project and a vrep container to run V-REP on any Linux.

RoboticsPy (README)

This project contains the basic structure to control a Pioneer P3DX robot on the V-REP simulator and read its sensors.

Robotics.jl (README)