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This project aims to solve the problem of inverse kinematics and vision reaching object by using neural networks

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Vision-guided reaching movements with NN

Introduction

This project aims: to solve the problem of inverse kinematics through the use of a neural network, locate the position of an object in space through a neural network and finally control the Iiwaa robotic arm to solve a reaching task.

This project was developed for the course of Robotics at the University of Pisa under the guide of Prof. Egidio Falotico.

All details can be found in the presentation here.

Table of Contents

Usage

This code requires Python 3.8 or later and ROS noetic:

# install ROS noetic
sudo apt install ros-noetic-desktop-full

# Add the following line at the end of $HOME/.bashrc: 
source /opt/ros/noetic/setup.bash

#install other packages
sudo apt install ros-noetic-{urdfdom-py,kdl-parser-py,ros-control,ros-controllers,gazebo-ros-pkgs,gazebo-ros-control}

download the repository and copy the src/kuka_iiwa folder in your catkin workspace:

#download repo
git clone https://github.com/alessandrocuda/Iiwa_vision_reaching_object
cd Iiwa_vision_reaching_object

#copy and compile the project under the catkin workspace
cp ./src/kuka_iiwa <path to your catkin workspace folder>
cd <path to your catkin workspace folder>
catkin_make
. devel/setup.bash

Now you are ready to run the gazebo enviroment

roslaunch kuka_iiwa_gazebo kuka_iiwa.launch

Then, be sure to start the simulation in gazebo and finally, start all ros nodes needed for the vision-reaching object task

# first run the vision service
rosrun kuka_iiwa_utilities iiwa_camera_service.py
# then from other terminal
cd ~/<path to your catkin workspace folder>/src/kuka_iiwa_utilities/script
rosrun kuka_iiwa_utilities iiwa_move_to.py

Contributing

  1. Fork it!
  2. Create your feature branch: git checkout -b my-new-feature
  3. Commit your changes: git commit -am 'Add some feature'
  4. Push to the branch: git push origin my-new-feature
  5. Submit a pull request :D

Contact

Alessandro Cudazzo - @alessandrocuda - alessandro@cudazzo.com

Giulia Volpi - giuliavolpi25.93@gmail.com

Nicola Ferella - n.farella@studenti.unipi.it

Project Link: https://github.com/alessandrocuda/Iiwa_vision_reaching_object

License

License

This library is free software; you can redistribute it and/or modify it under the terms of the MIT license.

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This project aims to solve the problem of inverse kinematics and vision reaching object by using neural networks

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