install-arduino-robot-arm install source code git clone https://github.com/kira-Developer/arduino_robot_arm.git Dependencies run this instruction inside your workspace:
ake sure you installed all these packages:
for kinetic distro
$ sudo apt-get install ros-kinetic-moveit $ sudo apt-get install ros-kinetic-joint-state-publisher ros-kinetic-joint-state-publisher-gui $ sudo apt-get install ros-kinetic-gazebo-ros-control joint-state-publisher $ sudo apt-get install ros-kinetic-ros-controllers ros-kinetic-ros-control for melodic distro
$ sudo apt-get install ros-melodic-moveit $ sudo apt-get install ros-melodic-joint-state-publisher ros-melodic-joint-state-publisher-gui $ sudo apt-get install ros-melodic-gazebo-ros-control joint-state-publisher $ sudo apt-get install ros-melodic-ros-controllers ros-melodic-ros-control for noetic distro
$ sudo apt-get install ros-noetic-moveit $ sudo apt-get install ros-noetic-joint-state-publisher ros-noetic-joint-state-publisher-gui $ sudo apt-get install ros-noetic-gazebo-ros-control joint-state-publisher $ sudo apt-get install ros-noetic-ros-controllers ros-noetic-ros-control Robot Arm The robot arm has 5 joints only 4 joints can be fully controlled via ROS and Rviz, the last joint (gripper) has a default motion executed from the Arduino code directly.
Circuit diagram
Robot initial positions
Configuring Arduino with ROS Install Arduino IDE in Ubuntu https://www.arduino.cc/en/software to install run $ sudo ./install.sh after unzipping the folder
Launch the Arduino IDE
Install the arduino package and ros library http://wiki.ros.org/rosserial_arduino/Tutorials/Arduino%20IDE%20Setup
Make sure to change the port permission before uploading the Arduino code $ sudo chmod 777 /dev/ttyUSB0
Usage Controlling the robot arm by joint_state_publisher $ roslaunch robot_arm_pkg check_motors.launch
You can also connect with hardware by running:
$ rosrun rosserial_python serial_node.py _port:=/dev/ttyUSB0 _baud:=115200
(Note: You may need to use ttyACM)
Simulation Run the following instructions to use gazebo
$ roslaunch robot_arm_pkg check_motors.launch $ roslaunch robot_arm_pkg check_motors_gazebo.launch $ rosrun robot_arm_pkg joint_states_to_gazebo.py (You may need to change the permission)
$ sudo chmod +x ~/catkin_ws/src/arduino_robot_arm/robot_arm_pkg/scripts/joint_states_to_gazebo.py
Controlling the robot arm by Moveit and kinematics $ roslaunch moveit_pkg demo.launch
You can also connect with hardware by running:
$ rosrun rosserial_python serial_node.py _port:=/dev/ttyUSB0 _baud:=115200
(Note: You may need to use ttyACM)
Simulation Run the following instruction to use gazebo
$ roslaunch moveit_pkg demo_gazebo.launch
Pick and place by using OpenCV Preparation Download webcam extension for VirtualBox
https://scribles.net/using-webcam-in-virtualbox-guest-os-on-windows-host/
Testing the camera and OpenCV Run color_thresholding.py to test the camera
Before running, find the camera index normally it is video0
$ ls -l /dev | grep video
If it is not, update line 8 in color_thresholding.py
8 cap=cv2.VideoCapture(0)
Then run
$ python color_thresholding.py
Using OpenCV with the robot arm in ROS In Real Robot In a terminal run $ roslaunch moveit_pkg demo.launch
this will run Rviz
connect with Arduino: select the Arduino port to be used on Ubuntu system
change the permissions (it might be ttyACM)
$ ls -l /dev | grep ttyUSB
$ sudo chmod -R 777 /dev/ttyUSB0
upload the code from Arduino IDE
$ rosrun rosserial_python serial_node.py _port:=/dev/ttyACM0 _baud:=115200
In another terminal $ rosrun moveit_pkg get_pose_openCV.py
This will detect blue color and publish the x,y coordinates to /direction topic
(Note: check the camera index and update the script if needed)
Open another terminal $ rosrun moveit_pkg move_group_node
This will subscribe to /direction topic and execute motion by using Moveit move group
The pick and place actions are performed from the Arduino sketch directly.
In simulation (Gazebo) In a terminal run $ roslaunch moveit_pkg demo_gazebo.launch
this will run Rviz and gazebo
In another terminal $ rosrun moveit_pkg get_pose_openCV.py
This will detect blue color and publish the x,y coordinates to /direction topic
(Note: check the camera index and update the script if needed)
Open another terminal $ rosrun moveit_pkg move_group_node
This will subscribe to /direction topic and execute motion by using Moveit move group
We can’t visualize the pick and place actions in gazebo
testing
