Quickstart¶
Install FIGAROH, run a real calibration on a bundled robot, and read its report. About five minutes.
1. Install¶
pip install figaroh
Enough for calibration and identification. Trajectory design needs cyipopt, which installs from conda only.
git clone https://github.com/thanhndv212/figaroh-plus figaroh
cd figaroh
conda env create -f environment.yml
conda activate figaroh-dev
pip install -e .
Includes cyipopt for trajectory design and the tools to build these docs.
2. Get the examples¶
Robots, data and runnable scripts live in a separate repository:
git clone https://github.com/thanhndv212/figaroh-examples
cd figaroh-examples/examples/ur10
3. Run a calibration¶
python calibration.py --calibrate-only --no-plot
FIGAROH loads the UR10 URDF and 29 measured poses, fits joint offsets and link geometry, and prints a quality report: condition number, RMSE before and after, and outliers.
4. Read the result¶
| Output | Where | What to look for |
|---|---|---|
| Terminal report | your shell | RMSE should drop; few or no outliers |
| Saved results | data/calibration/calibration_results_<timestamp>.npz |
input for --update-model, which exports a corrected URDF |
| HTML report | results/calibration_report.html (with --html-report) |
residual plots and parameter table, shareable as one file |
Done when the terminal shows post-calibration RMSE below the pre-calibration value.
Where next¶
-
Calibrate your robot
Plan, design, configure, fit and verify, with the choices at each step.
-
Identify dynamics
Masses, inertias and friction from motion and torque logs.
-
Add your robot
Scaffold a folder with URDF, config and a tools subclass.
-
Use an AI agent
Let a coding agent set up and run the task with FIGAROH's skills.