ROS 2 Hand-Eye Calibration Demos

This package provides a simulated environment using a UR robot (Universal Robots) and Gazebo, enabling users to test and understand the workflow of hand-eye calibration without real hardware.

Overview

This repository contains:

• Gazebo simulation of a UR robot (UR5/UR10)
• MoveIt 2 motion planning setup
• Hand-eye calibration setups (eye-in-hand and eye-to-hand)
• Example calibration patterns and configuration files

You can use this simulation to experiment with different calibration setups, camera placements, and patterns.

🛠️ Prerequisites

Supported Versions

• ROS 2 Distribution: Jazzy Jalisco
• Gazebo Version: Harmonic
• Ubuntu: 24.04 (recommended)

Install Dependencies

Make sure the following dependencies are installed:

sudo apt update
sudo apt install ros-jazzy-moveit \
                 ros-jazzy-ros-gz \
                 ros-jazzy-ros2-control \
                 ros-jazzy-ros2-controllers \
                 ros-jazzy-ur \
                 ros-jazzy-ur-simulation-gz \
                 ros-jazzy-moveit-py

Then build and source your workspace:

colcon build
source install/setup.bash

Note: The ros-rolling-ur package provides the Universal Robots (UR) description, control, and simulation interfaces required for this demo.

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🚀 Running the Simulation

To start the hand-eye calibration demo in simulation, use:

ros2 launch ur_handeye_simulation sim_moveit.launch.py handeye_setup:=eye_in_hand

Once launched, you should see:

• A Gazebo window with the UR robot and calibration pattern.
• A MoveIt RViz interface for planning and visualizing motion.

Parameters

handeye_setup — Defines the calibration configuration.

• eye_in_hand: The camera is attached to the robot’s end-effector.
• eye_to_hand: The camera is fixed in the world frame, observing the robot.

🧩 Customizing the Calibration Pattern

You can customize the calibration pattern used in simulation to match your preferred marker board (e.g., checkerboard, Charuco, AprilTag).

1. Prepare a pattern PNG file by converting from PDF to PNG a pattern generated with calib.io

2. Copy the pattern PNG file in the ur_handeye_simulation/models/textures folder

3. Modify the pattern xacro properties in ur_handeye_simulation/urdf/ur_handeye_workcell.urdf.xacro with the name of the desired pattern file

  <xacro:property name="pattern_width"   value="0.200"/>
  <xacro:property name="pattern_height"  value="0.200"/>
  <xacro:property name="pattern_texture" value="checker_200x200_8x9_20.png"/>

Acquisition pipeline

ros2 launch  ur_handeye_app handeye_data_control.launch.py joint_targets_dir:=path/to/joint/targets

ros2 run ur_handeye_app data_acquisition --ros-args -p use_sim_time:=true