Methods for Simultaneous Robot-World Hand-Eye Calibration: A Comparative Study

Ali, Ihtisham; Suominen, Olli; Gotchev, Atanas; Morales, Emilio Ruiz

doi:10.20944/preprints201906.0182.v1

Cited by 12 publications

(3 citation statements)

References 20 publications

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“…The transformation from the robot TCP to the camera coordinate frame t T c is known as hand-eye transformation. We have discussed in detail various approaches for hand-eye and robot-world-hand-eye calibration methods in an earlier study [26]. The aforementioned article can be studied for a thorough understanding of the methods and their MATLAB implementation.…”

Section: Problem Formulationmentioning

confidence: 99%

Multi-View Camera Pose Estimation for Robotic Arm Manipulation

et al. 2020

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This paper proposes a novel approach aimed at estimating the pose of a camera, affixed to a robotic manipulator, against a target object. Our approach provides a way to exploit the redundancy of the robotic arm kinematics by directly considering manipulator poses in the model formulation for camera pose estimation. We adopt a single camera multi-shot technique that minimizes the reprojection error over all the rigid poses. The results of the proposed method are compared to four other studies employing either monocular or stereo setup. The experimental results on synthetic and real data show that the proposed monocular approach achieves better and in some cases comparable results to the stereo approach. Moreover, the proposed approach is significantly more robust and precise compared to other methods.

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Section: Problem Formulationmentioning

confidence: 99%

Multi-View Camera Pose Estimation for Robotic Arm Manipulation

et al. 2020

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“…Although the calibration accuracy is high, the camera needs to be calibrated in advance, and the algorithm is complex and time-consuming. Ali et al proposed a solution using unit quaternions to represent rotation matrices in 2019 [12], which produced good results under realistic visual noise. Tian Pengfei et al proposed a hand-eye calibration method combined with model accuracy compensation in 2020 [13].…”

Section: Introductionmentioning

confidence: 99%

Survey of the key technologies of manipulator target grasping

Huang¹,

Yang²,

Xie³

et al. 2023

3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023)

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At present, the object grasping system of robot based on vision is one of the research hotspots, and it has a broad application prospect in industry, especially in the part of sorting. The key technologies of this system include robot hand-eye calibration, grasping target detection, grasping path planning, etc. This paper provides an overview about the current status of these key technologies by collating relevant literature, including the four kinds of hand-eye calibration methods, deep learning based grasping target detection algorithms, and the advantages and disadvantages of three kinds of grasping path planning methods. In this paper, the key technologies of vision-based robot object grasping system are summarized and prospected, which can be helpful to researchers in related fields.

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“…[34]. Typically, separate solution based on Kronecker product has good rotation accuracy; however, the position accuracy is often compromised [35], while the Kronecker product and the dual quaternions can also be applied to solve rotation and translation simultaneously [36]. The probabilistic method was also applied on robot-world and hand-eye calibration [37].…”

Section: Introductionmentioning

confidence: 99%

Optimal robot-world and hand-eye calibration with rotation and translation coupling

Wang

Song

2022

Robotica

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A classic hand-eye system involves hand-eye calibration and robot-world and hand-eye calibration. Insofar as hand-eye calibration can solve only hand-eye transformation, this study aims to determine the robot-world and hand-eye transformations simultaneously based on the robot-world and hand-eye equation. According to whether the rotation part and the translation part of the equation are decoupled, the methods can be divided into separable solutions and simultaneous solutions. The separable solutions solve the rotation part before solving the translation part, so the estimated errors of the rotation will be transferred to the translation. In this study, a method was proposed for calculation with rotation and translation coupling; a closed-form solution based on Kronecker product and an iterative solution based on the Gauss–Newton algorithm were involved. The feasibility was further tested using simulated data and real data, and the superiority was verified by comparison with the results obtained by the available method. Finally, we improved a method that can solve the singularity problem caused by the parameterization of the rotation matrix, which can be widely used in the robot-world and hand-eye calibration. The results show that the prediction errors of rotation and translation based on the proposed method be reduced to $0.26^\circ$ and $1.67$ mm, respectively.

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Methods for Simultaneous Robot-World Hand-Eye Calibration: A Comparative Study

Cited by 12 publications

References 20 publications

Multi-View Camera Pose Estimation for Robotic Arm Manipulation

Multi-View Camera Pose Estimation for Robotic Arm Manipulation

Survey of the key technologies of manipulator target grasping

Optimal robot-world and hand-eye calibration with rotation and translation coupling

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