Calibrating hand tracking to your own hand — with real data from a live session

contact@mulhamfetna.com (Mulham Fetna) — Wed, 16 Sep 2026 00:00:00 +0000

The shipped thresholds were measured on one hand with one webcam. Here is how to measure yours — and what a live recording revealed about how far off “good enough” can be while the twin still looks perfect.

Symptoms that call for calibration
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What you see in the published flexions	Cause	Change
A fist, but flexion stays below 1.0	your fist angle is above the curled limit	raise `*_CURLED_ANGLE` to your fist reading
Flexion hits 1.0 with the hand half closed	curled limit too high	lower `*_CURLED_ANGLE`
Flexion above 0 with a relaxed open hand	your open angle is below the straight limit	lower `*_STRAIGHT_ANGLE` to your open reading
The thumb flickers	thumb window too narrow for your jitter	widen it (Part 8)

Calibrate against the numbers, not the render. With the current force-control tuning, the simulated finger snaps shut past flexion ≈ 0.51 (Part 11), so most calibration errors are invisible in the viewer. Watch ros2 topic echo /hand/target_flexions.

Real data: what a live session produced
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MuJoCo’s viewer has a Control panel showing the live force of every motor. Since the force is $F = 50 - 100 \cdot \text{flexion}$, every recorded frame gives back the exact flexion the tracker published: flexion = (50 − F) / 100.

Run the tendon-driven hand digital twin in 10 minutes

contact@mulhamfetna.com (Mulham Fetna) — Wed, 16 Sep 2026 00:00:00 +0000

Clone, run one setup script, run one Compose command — and a webcam window and a MuJoCo viewer open side by side, with a simulated hand that closes when you close yours. Here are four ways in, from the full stack down to the bare model.

The goal of this article: both windows open, and the twin follows your hand.

What you need
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Requirement	Check with	Notes
Linux desktop, X11 or XWayland	`echo $DISPLAY` → `:0`	Wayland sessions work through XWayland
Docker Engine + Compose v2	`docker compose version`	Built with Docker 29.8 / Compose 5.5
A webcam	`ls /dev/video0`	Close any other app using it
GPU device nodes	`ls /dev/dri`	Intel/AMD out of the box; NVIDIA needs the container toolkit (Part 18)
~5 GB of disk		images: vision 2.9 GB, twin 1.7 GB

No ROS installation is needed on the host — ROS 2 Jazzy lives inside the containers.

Four ways to run it
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git clone https://github.com/mulhamfetna/ros2-tendon-driven-hand-mujoco-digital-twin-vision-teleoperation.git
cd ros2-tendon-driven-hand-mujoco-digital-twin-vision-teleoperation

./setup_host.sh              # X11 access for the containers + camera/GPU checks (once per login)
docker compose up --build    # builds both images, starts vision_tracker and mujoco_twin

Stop with Ctrl+C, then docker compose down to release the camera.

Tutorial on Mulham Fetna

Calibrating hand tracking to your own hand — with real data from a live session

Symptoms that call for calibration #

Real data: what a live session produced #

Run the tendon-driven hand digital twin in 10 minutes

What you need #

Four ways to run it #

Symptoms that call for calibration
#

Real data: what a live session produced
#

What you need
#

Four ways to run it
#