Humanoid robot programming

The first part of the subject aims to get you acquainted with programming of a humanoid robot. We will use a Python simulator of humanoid robot iCub.

Lab 1

PyBullet documentation can be useful and can be found here.

Installation

Using venv is suggested: python3 -m venv pycub_venv && source pycub_venv/bin/activate and then
- On Linux (and possibly windows) the best way is probably to just do: python3 -m pip install icub_pybullet
- Alternatively, git clone https://github.com/rustlluk/pyCub.git, cd pyCub/icub_pybullet and python3 -m pip install .
  - In theory, you do not need to install it. All HWs should work without installation, if you run then from the correct folder. You need to install dependencies by hand, though
MACs with ARM procesors may have problems with installing open3d. You can either:
- Install open3d from source. Check https://github.com/rustlluk/pyCub/blob/master/Docker/Dockerfile and https://www.open3d.org/docs/release/arm.html
- Use VNC DockerVNC Docker
- Use Gitpod (ONA). Use gitpod. Open https://app.gitpod.io/#https://github.com/rustlluk/pycub (you will need github account). The first run can take some time, but after that you should see an environment inside a virtualized system. The performance is not great, but if you change simulation speed (in client.update_simulation(time)) it is fine. t = 0.025 seems to work okay. The code is already downloaded and installed in /home/gitpod/pycub
  - you will be asked to select web interface or to open using plugins to vscode or PyCharm
- Use lab computers

With python3.8 (and maybe 3.9) you need to call python3 -m pip install –upgrade pip and

python3 -m pip install -U –trusted-host www.open3d.org -f http://www.open3d.org/docs/latest/getting_started.html open3d

before running pip install. Copying from this tends to change two dashes (-) after each other as a long dash, update it in the terminal then.

More info can be found on Github or this presentation.

If you have errors with “Index out of range” on windows, please reinstall the library.

To test whether everything works fine run python3 -m icub_pybullet.examples.push_the_ball_cartesian and you should see robot hitting a ball from a table.

The first run can take a long time because of VHACD meshes creation.

Lab Computers

The computers in the lab should be powerful enough to run the code. You can install the same way (create venv, install icub_pybullet from pip).

When turning on the lab computers you need to select Linux Bookworm (13133, …) and then log in with CTU username and password

Running bugs solutions

Use Python 3.8-3.12
if you are using conda (or similar) install the packages using 'conda install …' and not 'python -m pip install …'. These two are not the even though it may look like it
do not use conda (use python venv or install into global environment). Be sure to do 'conda deactivate' first
if you use IDE (pycharm, vscode) try to run it also in normal terminal outside the IDE. IDEs sometimes replace system variables which can cause problems with graphical things
use open3D web visualizer. Set gui.web in config to True (and gui.standard to False)

iCub Kinematics

This picture shows the joints of iCub with their names and indexes that can be used to control the robot in joint space in the PyCub simulator.

PyCub

The simulator is written in Python3 and uses PyBullet as a physics engine and Open3D for visualization. It should run without problem on any system with Python3 (it is tested in Python3.11; anything over 3.8 should be fine; the theoretical lower limit is 3.6 because of f-strings and upper limit 3.12 because some dependencies).

The whole documentation can be found here.

A presentation with a description of basic functionality can be found here.

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