Laser-Based Kinematic Calibration of Robot Manipulator Using Differential Kinematics

Park, Inwon; Lee, Bum‐Joo; Cho, Se-Hyoung; Hong, Young-Dae; Kim, Jong-Hwan

doi:10.1109/tmech.2011.2158234

Cited by 86 publications

(49 citation statements)

References 22 publications

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“…However, the upper body cannot be calibrated with such a method as the corresponding joints do not affect the IMU measurements. Park et al [2] use optimization of the Denavit-Hartenberg parameters of a manipulator using a laser attached to the end-effector and an external camera within a Kalman-Filter framework. While this allows for precise measurements, it also requires a substantial modification of the hardware.…”

Section: Related Workmentioning

confidence: 99%

Whole-body self-calibration via graph-optimization and automatic configuration selection

Maier

Wrobel

Bennewitz

2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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In this paper, we present a novel approach to accurately calibrate the kinematic model of a humanoid based on observations of its monocular camera. Our technique estimates the parameters of the complete model, consisting of the joint angle offsets of the whole body including the legs, as well as the camera extrinsic and intrinsic parameters. We cast the parameter estimation as a least-squares optimization problem. In the error function, we consider the residuals between camera observations of end-effector markers and their projections into the image based on the estimate of the calibration parameters. Furthermore, we developed an approach to automatically select a subset of configurations for the calibration process that yields a good trade-off between the number of observations and accuracy. As the experiments with a Nao humanoid show, we achieve an accurate calibration for this low-cost platform. Further, our approach to configuration selection yields substantially better optimization results compared to randomly chosen viable configurations. Hence, our system only requires a reduced number of configurations to achieve accurate results. Our optimization is general and the implementation, which is available online, can easily be applied to different humanoids.

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Section: Related Workmentioning

confidence: 99%

Whole-body self-calibration via graph-optimization and automatic configuration selection

Maier

Wrobel

Bennewitz

2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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“…The main methods to estimate the parameter errors include linear least square method [7,15], Levenberg-Marquardt (LM) method [16][17][18], Kalman filter [9,19] and artificial neural networks [20,21]. The model-based method can achieve a good calibration effect since the kinematic model is fitted to match the real one.…”

Section: Introductionmentioning

confidence: 99%

Positional error similarity analysis for error compensation of industrial robots

Zeng

Tian

Liao

2016

Robotics and Computer-Integrated Manufacturing

108

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“…The improving robot accuracy has been performed by the conventional robot kinematic calibration method. A system of linear or non-linear differential equations is derived based on the measurements of robot end-effector position and its joint angle position [1][2][3][4][5][6][7]. A persistent problem is to find external sensors which can measure the robot position accurately and precisely.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Robot Calibration Performance based on a Three Dimensional Small Displacement Measuring Sensor

Nguyen¹,

Kang²

2014

Journal of Institute of Control, Robotics and Systems

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There have been many autonomous robot calibration methods which form closed loop structures through the various attached sensors and mechanical fixtures. Single point calibration among them has been used for on-site calibration due to its convenience of implementation. The robot can reach a single point with infinitely many configurations so that single point calibration algorithm can be set up and easily implemented relative to the other methods. However, it is not still easy to drive the robots' sharp edge to its corresponding edge of the fixture. This is error-prone process. In this paper, we propose a 3 dimensional small displacement measuring sensor and a robot calibration algorithm based on this sensor. This method relieves the difficulty of matching two edges in the single point calibration and improves the resulting robot accuracy. Simulated study is carried out on a Hyundai HA06 robot to show the effectiveness of the proposed method over the single point calibration. And also, the resulting robot accuracy is compared with that from 3D laser tracker based calibration to show the dependency of robot accuracy on range of the workspace where the measurement data are collected.

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Laser-Based Kinematic Calibration of Robot Manipulator Using Differential Kinematics

Cited by 86 publications

References 22 publications

Whole-body self-calibration via graph-optimization and automatic configuration selection

Whole-body self-calibration via graph-optimization and automatic configuration selection

Positional error similarity analysis for error compensation of industrial robots

Evaluation of Robot Calibration Performance based on a Three Dimensional Small Displacement Measuring Sensor

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