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gelsightinc / gsrobotics

GelSight SDK for robotic sensors
GNU General Public License v3.0
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SDK for GelSight robotic sensors

This respository contains python code to connect to the GelSight Mini. The code enables basic functionalities, such as view and save data (images or video) from these devices, and example code to get 3D point cloud data derived from 2D images.

About to update instructions

Prerequisites

Windows

Cloning the repository

On Windows, we recommend running the examples within the PyCharm development environment. Here are instructions on how to set up PyCharm.

  1. Download and install Git for Windows

  2. Download and install TortoiseGit. For most users, the correct version is 64-bit Windows. Run the First Start wizard after installation and choose the default options.

  3. Download and install Python 3.10. More recent versions of Python might require additional steps to install the packages used by this codebase. For most users, the correct version is Windows installer (64-bit)

  4. Go to PyCharm and download the PyCharm Community installer

  5. Clone this repository

    1. Navigate to a folder on your machine where you would like to clone the repository
    2. On this page, click the green Code button at the top and copy the repository URL by clicking the button to the right of the URL.
    3. In Windows Explorer, right-click in the folder and choose Git Clone... On Windows 11, you will have to choose "Show More Options"
      TortoiseGit menu Windows 11 contextual menu
      Git Clone using TortoiseGit Need to click Show More Options on Windows 11
    4. Clone the repository to a folder on your local machine
      TortoiseGit settings
      Clone repository using TortoiseGit

Configuring PyCharm

  1. Plug in the GelSight Mini device to a USB port on your computer. The lights should turn on.
  2. Launch PyCharm and Open the gsrobotics folder you cloned following the instructions above. Choose Trust Project when prompted.
  3. The first time you open the gsrobotics folder, PyCharm will prompt you to create the virtual environment. This will automatically install the packages listed in the requirements.txt file. Click OK to create the environment.
    TortoiseGit settings
    Create the virutal environment in PyCharm
  4. From the file navigator on the left, open the script showimages.py in the examples folder. Right-click in the file editor and choose Run 'showimages'.
    TortoiseGit settings
    Run showimages.py in PyCharm
  5. You should see a window with a live view from the camera in the GelSight Mini. Press the Mini into an object to see a live tactile image.
  6. Congratulations, you are now able to program your GelSight Mini!

Live 3D Demo

  1. These instructions assume you have successfully installed Python, PyCharm and run the showimages.py demo above.
  2. Open the show3d.py script
  3. Right-click in the file editor and choose Run 'show3d'.

https://github.com/gelsightinc/gsrobotics/assets/44114954/85b3e123-730d-4dfa-a05a-983dfc1e5a78

  1. Congratulations, you are now able to run the 3D demo using GelSight Mini!

Linux

Python 3.8 or above

Install python libraries

pip3 install .
or 
pip3 install . --upgrade

Note this step does not install the ROS or ROS2 related libraries required by the python scripts in examples/ros folder of this repository yet. Please follow the installation guide of those seperately.

Set paths

PYDIR=`pip3 show gelsight | grep -i location | cut -f2 -d" "`
export PYTHONPATH=$PYDIR/gelsight:$PYTHONPATH

More Examples

Mini Marker Tracking

There are multiple marker tracking demos. Each uses a different marker tracking algorithm. You can find all of them in the demo directory.

Mini ROS and ROS2

Prerequisites

Install ROS or ROS2 , see ROS Documentation for instructions. The example code uses cv_bridge which can be installed using:

sudo apt-get install ros-${ROS_DISTRO}-cv-bridge

For example, on Ubuntu 20, 

To install cv-bridge for ROS

    sudo apt-get install ros-noetic-cv-bridge

To install cv-bridge for ROS2

    sudo apt-get install ros-foxy-cv-bridge

The showimages examples publish to the ROS topic /gsmini_rawimg_0

The show3d examples publish to the ROS topic /pcd

They can be viewed in rviz or rviz2

ROS examples

source /opt/ros/noetic/setup.bash
cd examples/ros
roscore
python3 showimages_ros.py
python3 show3d_ros.py
rviz -d mini_ros_3d_config.rviz

ROS2 examples

source /opt/ros/foxy/setup.bash
cd examples/ros
python3 showimages_ros2.py
python3 show3d_ros2.py
rviz2 -d mini_ros2_3d_config.rviz

Device setup

The camera on the GelSight Mini is a USB camera.

If you need to adjust the camera settings for your application, you can change the camera parameters using any app or library that can control UVC cameras.

Linux camera settings

A popular library is v4l2-ctl. To install this library on ubuntu run, 

sudo apt-get update
sudo apt-get -y install v4l-utils

Refer to file config/mini_set_cam_params.sh present in this repository to view/edit all the available camera parameters. You can list the devices by running:

v4l2-ctl --list-devices

In most cases when you have one Mini connected to your computer, the device ID is usually 2, because the webcam on your computer is always on device ID 0.

Windows camera settings

On Windows, you can use the AMCap app to configure the camera settings, see https://docs.arducam.com/UVC-Camera/Quick-Start-for-Different-Systems/Windows/

Possible errors

With cv2

pip uninstall opencv-python-headless

With Docker container

sudo apt-get install libopenjp2-7
sudo apt-get install qt5-default
pip3 install opencv-python==4.1.2.30
sudo apt-get install libopenexr-dev

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Contact

This package is under active development. Contact support@gelsight.com if have any questions / comments / suggestions.