Hand-Eye Calibration

Introduction

핸드-아이 칼리브레이션은 카메라(“눈”)가 보는 것과 로봇 팔(“손”)이 움직이는 위치를 연결하는 데 사용됩니다.

Eye-in-hand calibration

A process for determining the position and orientation of a statically mounted camera with respect to the robot’s base frame. It is usually done by placing an object of known geometry in the robot’s gripper, followed by taking a series of images of it in a set of different positions and orientations.

Eye-to-hand calibration

A process for determining the relative position and orientation of a robot-mounted camera with respect to the robot’s end-effector. It is usually done by capturing a set of images of a static object of known geometry with the robot arm located in a set of different positions and orientations.

Articles & Tutorials

• Hand-Eye Calibration Concept and Theory
• Zivid Calibration Object
• How to run and integrate Zivid Hand-Eye Calibration
• How to get Good Dataset for Hand-Eye Calibration
• Cautions and Recommendations for Hand-Eye Calibration
• How to Verify Hand-Eye Calibration
• How to troubleshoot Hand-Eye Calibration
• How To Use the Result of Hand-Eye Calibration

Where to Start?

Learning

• Hand-Eye Calibration Concept and Theory

  Covers the concept and theory of hand-eye calibration without going into the details of the Zivid hand-eye calibration software. If you already have the theoretical background and are looking for a practical guide on how to perform hand-eye calibration with Zivid software, skip to the following tutorials.

Doing

• How to select Zivid Calibration Object

  Outlines the available Zivid Hand-Eye calibration object options and provides advice on choosing and preparing the calibration object for accurate calibration.

• How to run and integrate Zivid Hand-Eye Calibration

  Provides an overview of the Zivid tools and code samples available to perform the calibration and helps to select the best one for your use case.

• How to get Good Dataset for Hand-Eye Calibration

  Explains the process and provides tips to prepare the robot and camera and collect high-quality point clouds and robot pose data to ensure satisfactory hand-eye calibration results.

• Cautions and Recommendations for Hand-Eye Calibration

  Thoroughly covers common pitfalls, best practices, and recommendations to avoid mistakes during calibration and get a satisfactory result.

• How to Verify Hand-Eye Calibration

  Covers and explains available methods for checking that the computed hand-eye transform is accurate and recommends the best verification method.

• How to troubleshoot Hand-Eye Calibration

  Guidance on diagnosing and fixing problems if hand-eye calibration fails or if the results are unsatisfactory.

• How To Use the Result of Hand-Eye Calibration

  Explains how to apply the calculated hand-eye transform in robotics applications by computing a pose for a robot guidance task, e.g., picking an object.

Version History

SDK	Changes
2.16.0	더 작은 Zivid calibration board ZVDA-CB02 (5x6 20 mm) 에 대한 지원이 추가되었습니다.
2.15.0	Hand-eye GUI가 추가되었습니다.
2.13.0	ArUco 마커에 대한 지원이 추가되었습니다.
2.6.0	Blooming - Bright Spots in the Point Cloud 에 관련하여 체커보드 감지의 견고성 향상 .
2.4.0	핸드-아이 칼리브레이션은 정확도를 개선하기 위해 업데이트 되었습니다. 회전 잔차를 약간 증가시키면서 병진 잔차를 약 50(%) 개선하였습니다.
2.3.0	체커보드 감지의 견고성이 향상되었습니다.
2.2.0	Zivid 공식 Calibration board의 새로운 라인에 대한 지원이 추가되었으며, 그 첫 번째는 ZVDA-CB01 (7x8 30 mm) 입니다.
2.0.0	Hand-eye API가 Calibration 네임스페이스의 일부로 변경되었습니다.
1.6.0	Hand-eye 칼리브레이션 API가 추가되었습니다.