IFL-CAMP/easy_handeye

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1172 stars · 254 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A ROS package with a GUI that automates hand-eye calibration between a robot and a camera/tracking system, supporting eye-in-hand and eye-on-base setups using OpenCV algorithms like Tsai-Lenz. It samples poses via tf, computes the calibration matrix, stores it, and republishes the result as a tf transform at startup.

Use cases

• calibrate a camera mounted on a robot end-effector (eye-in-hand)
• calibrate a fixed external camera relative to a robot base (eye-on-base)
• publish hand-eye calibration results as a tf transform in ROS
• evaluate the accuracy of an existing hand-eye calibration
• automate robot pose sampling for calibration with MoveIt
• calibrate a robot with an AR marker tracking system

When to choose

• you use ROS1 and need an automated, hardware-independent hand-eye calibration
• you want a GUI-driven workflow to sample, compute, store, and publish calibration
• you need multiple algorithm options (Tsai-Lenz, Park, Horaud, Andreff, Daniilidis)
• you want calibration results automatically kept up-to-date across system startups

When to avoid

• you need a ROS2-native solution (use easy_handeye2 instead)
• you are not working within the ROS/tf ecosystem
• you need calibration for non-robotic camera setups without a robot

Facets

library · maturity active

computer-vision robotics gui developer-tools robotics computer-vision python hand-eye-calibration ros tf opencv eye-in-hand eye-on-base moveit camera-calibration automation linux

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For agents

markdown · JSON · MCP: product_card(name="IFL-CAMP/easy_handeye")