I See You

Package that will allow you to control 4 separate dynamixels as if there were eyes! [Checkout the video here]

Here's a sample pic of the eyes:

Hardware requirements

What you will need is:

• Dynamixel AX-12A (I used 4, but you can use as many as you want).

• USB to Dynamixel converter.

• 6 Port AX/MX Power Hub.

• 12 V power supply (at least 1 A).

• Webcam (The one used is a Logitech C930).

Software requirements

This packages were tested with:

• Ubuntu 16.04 LTS and Ubuntu 18.04 LTS.

• ROS kinetic with the following packages:

  • dynamixel control

  • vision-opencv

• CUDA 9.0.

• Tensorflow (versions 1.5 and 1.9):

  • You will need to install Tensorflow's Object Detection API.

• OpenCV (for C++ and Python 2.7)

• Deep Learning Library (DLib) for C++ (version 19.10).

  • If you want to use another version of DLib, you will need to change the CMakeLists.txt from eyecu package. Specifically change this line:

  add_subdirectory($ENV{HOME}/cmake_workspace/dlib-<VERSION>/dlib dlib_build)

• Boost library.

Notes on DLib

To compile the project with DLib, you'll need to do the following steps:

foo@bar:~$ cd $HOME
foo@bar:~$ mkdir cmake_workspace && cd cmake_workspace
foo@bar:~$ wget http://dlib.net/files/dlib-19.15.tar.bz2
foo@bar:~$ tar -xf dlib-19.15.tar.bz2
foo@bar:~$ rm -rf dlib-19.15.tar.bz2 (optional)

Launch the main file

Once you are able to compile, you can launch the whole system by typing:

foo@bar:~$ roslaunch eyecu start_dynamixel_tracking_tensorflow.launch (for tensorflow)
or
foo@bar:~$ roslaunch eyecu start_dynamixel_tracking.launch (for OpenCV or Dlib)

Notes on this version

This version doesn't use Lidar or Pointcloud. If you want more accuracy in your measurements you can checkout v1.5-lidar-camera.

Credits

This work was inspired by Lentin Joseph's dynamixel tracking package.