Tutorials¶
These walkthroughs explain the why and how behind FIGAROH's four core workflows, using TIAGo (a mobile manipulator) as the running example. Each one is backed by a real, runnable script in figaroh-examples — see the Examples Gallery for the complete per-robot reference implementations (UR10, TIAGo, TALOS, Staubli TX40) once you've read the walkthrough for the workflow you need.
| Tutorial | Workflow | Answers |
|---|---|---|
| Calibration Walkthrough | Kinematic calibration | Why do robots need calibrating, and how does FIGAROH solve for the correction? |
| Choosing What to Estimate | Kinematic calibration | Which corrections should I estimate, and how, for my robot and postures? |
| Identification Walkthrough | Dynamic parameter identification | How does FIGAROH turn a torque/motion log into a validated dynamic model? |
| Optimal Experiment Design | Optimal configurations & trajectories | How does FIGAROH decide which poses/motions to measure, instead of guessing? |
Starting with a new robot or dataset¶
Begin with Plan, Fit and Validate to inventory data, choose the model/methods, design acquisition, process measurements and establish independent validation. These task walkthroughs start after those decisions; the examples repository supplies a reusable experiment brief and integration guide.
Prerequisites¶
- FIGAROH installed (see Getting Started)
- A robot URDF and a unified config for it — or clone figaroh-examples and use one of the shipped robot folders directly
- Basic familiarity with the linear-in-parameters formulation
τ = W(q, q̇, q̈) · φfor dynamics; geometric calibration instead fits pose/contact residuals and analyzes their parameter Jacobian
The four workflows, at a glance¶
Optimal Configuration Generation ──▶ (collect calibration data) ──▶ Kinematic Calibration
Optimal Trajectory Generation ──▶ (collect identification data) ──▶ Dynamic Identification
The two design steps are optional tools for choosing informative, feasible experiments (see Optimal Experiment Design). Acquisition coverage, synchronization and sensor quality still limit the resulting fit.
Use verification and HTML reports where supported by the selected workflow — see Reporting & Verification. Inspect skipped checks and actual held-out data; a passing verdict alone is not proof of a validated model.