An iterative approach in pose measurement through hand-eye calibration

Muis, Abdul; Kouhei, Ohnishi

doi:10.1109/cca.2003.1223144

Cited by 6 publications

(4 citation statements)

References 12 publications

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“…In the eye-in-hand configuration the image of the object is dependent on the pose of the end-effector. This configu-ration is the most popular method of visual servoing and has been extensively described in [2] and [3]. In the eyeto-hand configuration the image of the target is independent of the robot motion.…”

Section: B Stereo Camera Locationmentioning

confidence: 99%

Autonomous Stereo Camera Parameter Estimation for Outdoor Visual Servoing

Ziraknejad

Tafazoli

Lawrence

2007

2007 IEEE Workshop on Machine Learning for Signal Processing

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In the majority of vision applications, sensor calibration is a prerequisite to proper use of the sensor for both measurement and control. The objective in camera calibration is to estimate a set of parameters to construct a mapping between the 3D position of a target point and its 2D image coordinates. In this paper an autonomous stereo camera calibration technique with applications in industrial outdoor visual servoing systems is presented. The stereo camera model obtained was used to estimate the pose of the target object during the robot servoing process. The heavy-duty stereo camera rig was installed on the torso of an outdoor 3DOF robotic manipulator. An efficient iterative leastsquares parameter estimation algorithm was used to estimate the transformation parameters between the 3D world coordinates of the target object and its 2D image coordinates in the stereo image planes.The stereo camera calibration is entirely an autonomous process as the robot moves the calibration tool within its workspace and the stereo camera model is produced after the data collection process. The stereo cameras are treated as a single unit and a single transformation is obtained for the stereo camera pair in the system. The calibration process is fast, efficient and no human interaction is required during the process.

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Section: B Stereo Camera Locationmentioning

confidence: 99%

Autonomous Stereo Camera Parameter Estimation for Outdoor Visual Servoing

Ziraknejad

Tafazoli

Lawrence

2007

2007 IEEE Workshop on Machine Learning for Signal Processing

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“…Non-linear optimization can be used to solve the rotation and translation components simultaneously as shown in [3], [4] and [5], yielding more stable results by minimizing errors caused by model inaccuracies.…”

Section: Introductionmentioning

confidence: 99%

A low cost hand-eye calibration method for arc welding robots

Dinham¹,

Fang²

2009

2009 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Hand-eye calibration is one of the most important and fundamental tasks in performing visual guided robot control tasks. Many techniques have been proposed that use various expensive equipment ranging from a three dimensional positioning device to a laser measurement device. The work presented in this paper aims at developing a low cost robot hand/eye calibration method that is accurate and robust enough to be used in a robotic arc welding system. The proposed calibration method allows the camera and object frames to be referenced directly to the robots base co-ordinate frame. Experimental results show that the developed method can be used to achieve a calibration accuracy of 1 mm (in the directions of interest, X and Y axes) that is acceptable for robotic welding applications.

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“…This ability depends on the ability of its vision system to provide accurate data. Furthermore, the spatial relationship between camera and object needs be obtained through camera calibration [1]. In [2], a stereo vision calibration procedure based on a laser line projection plane was presented.…”

Section: Introductionmentioning

confidence: 99%

Machine Vision-Based Automatic Placement System for Solenoid Housing

Ho¹,

Chen²,

Tien

et al. 2015

KEM

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This paper proposes a machine vision-based, servo-controlled delta robotic system for solenoid housing placement. The system consists of a charge-coupled device camera and a delta robot. To begin the placement process, the solenoid housing targets inside the camera field were identified and used to guide the delta robot to the grabbing zone according to the calibrated homography transformation. To determine the angle of solenoid housing, image preprocessing was then implemented in order to rotate the target object to assemble with the solenoid coil. Finally, the solenoid housing was grabbed automatically and placed in the collecting box. The experimental results demonstrate that the proposed system can help to reduce operator fatigue and to achieve high-quality placements.

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An iterative approach in pose measurement through hand-eye calibration

Cited by 6 publications

References 12 publications

Autonomous Stereo Camera Parameter Estimation for Outdoor Visual Servoing

Autonomous Stereo Camera Parameter Estimation for Outdoor Visual Servoing

A low cost hand-eye calibration method for arc welding robots

Machine Vision-Based Automatic Placement System for Solenoid Housing

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