Calibration of robot kinematics

Have you ever wondered why the accuracy of your robot is poor, and why the end-effector is at different poses when you move in the null-space? Well, the platonics did! And we are you to help you out. This problem is especally relevant when working with cartesian control where an accurate forward kinematics is desirable.

The method implemented in this repository was mainly developed for the Franka Emika Panda robot, where inaccurate kinematics have been raised a few times.

The technique and code used here can also be used to determine mount positions of robots on different tables or other robots.

The calibration tool

Installation

Install the package through pip, using

pip3 install .

Install the package through poetry, using

poetry install

Install the ros workspace to record data. It is only running one script to echo joint states and writing a csv file. There is hardly any dependencies on this.

cd ros_ws
catkin build
source devel/setup.{bash,zsh}

Record the data

The calibration is done in two steps. First, the robot is moved to a few poses, and the joint states are recorded. This is done by running the record_joint_states_dataset script.

Here is an example for calibrating the kuka for example:

rosrun calibration_tools record_joint_states_dataset --joint-state-topic-name /joint_states --robot-name kuka_1  --tool-position-on-table front --robot-dof 7 

• Press 'a' to add a new joint configuration that has the sphere in the hole tha the algorithm
• Presss 'd' to delete the last joint configuration from the list
• Press 's' when you switch the hole in which you are recording
• Press 'q' when you have finished recording

Record data with a Franka

rosrun calibration_tools record_joint_states_panda --joint-state-topic-name /joint_states --robot-name panda_1 --config-file panda_1.yaml --tool-position-on-table front 

• Press 'check' to add a data point
• Press 'down' to delete the last data point
• Press 'o' to switch between holes
• Press 'x' to save the data and quit. You need to create a config file for the /src/calibration_tools/config/

Calibrate the urdf model

The second step is the optimization. Make sure you have activated your virtual environment if you use one (source bin/activate, poetry shell). Go to the scripts folder and run the optimization script.

cd scripts
python3 run_optimizer.py --urdf <path/to/urdf> --data <path/to/data/folder> 

To get the full list of arguments, run the following command:

python3 run_optimizer.py --help

This script runs the optimazation and prints the result. It outputs a new urdf in the asset folder with the optimized parameters. KPI's are stored in the output folder (default is output).

Evaluate a calibration

You can evaluate the calibration by runnig.

cd examples
python3 eval_model.py --urdf-file <path/to/urdf> --evaluate-on <path/to/data/folder> 

This scripts produces the kpis. By passing the -s flag, you can show the robot. By passing the --overlay flag an overlay of all the configuration is saved to the output folder.

To get all the potential arguments, run the following command:

python3 eval_model.py --help