An automated method to calibrate industrial robot kinematic parameters using Spherical Surface constraint approach

Liu, Yong; Shi, Dingbing; Ding, Jianguo

doi:10.1109/cyber.2014.6917491

Cited by 8 publications

(5 citation statements)

References 9 publications

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“…For robots, many researchers proposed a scheme to identify the D-H parameters from the measurement of the end effector position. For easier and lower-cost measurement, some researchers presented the measurement of the end effector position when it is nominally constrained at a point [10], [11], on a line [12], on a spherical surface [13,14], or on a plane [15]. Recently, more researches employ either a laser tracker [16,17] or a vision-based measurement system [18][19][20], which can measure the end effector's 3D position at arbitrary positions over the entire workspace.…”

Section: Prior Artmentioning

confidence: 99%

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Novel kinematic model of a SCARA-type robot with bi-directional angular positioning deviation of rotary axes

Zhao

Ibaraki

2022

Int J Adv Manuf Technol

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This paper proposed a kinematic model and its calibration scheme to further improve an industrial robot's absolute positioning accuracy over the entire workspace. To demonstrate the proposed model and its effectiveness in simplified kinematics, this paper only targets a SCARA (Selective Compliance Assembly Robot Arm) -type robot. The proposed model includes not only link length errors and rotary axis angular offsets, widely known as the Denavit-Hartenberg (D-H) parameters, but also the "error map" of the angular positioning deviation of each rotary axis, modelled as a function of command angular position, and the rotation direction to model the influence of backlash. The angular positioning deviation of each rotary axis is identified by measuring the robot's end-effector position by a laser tracker with indexing each rotary axis at prescribed angular positions. To verify the validity of the identified model, the effectiveness of the compensation based on it is experimentally investigated. By the compensation, the robot's average absolute position error was reduced by 33% to 0.034mm. Furthermore, this paper experimentally demonstrates that the proposed model can be extended to the radial error motion, axis-to-axis cross talk, and the three-dimensional positioning with orientation errors of axis average lines.

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Section: Prior Artmentioning

confidence: 99%

“…The length errors of the first and second links, ∆L 1 and ∆L 2 , can be calculated by Eqs. (12) and (13).…”

Section: Identification Of Bidirectional Angular Position Deviation O...mentioning

confidence: 99%

Novel kinematic model of a SCARA-type robot with bi-directional angular positioning deviation of rotary axes

Zhao

Ibaraki

2022

Int J Adv Manuf Technol

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“…across all robot configurations. This metric is sensitive to all sources of error including registration error, joint-offset error, measurement error, and other unmodeled robot factors as discussed in Section I. Consequently, the actual robot accuracy is less than e as calculated in (18) since a robot's accuracy would only depend on joint-offset error and unmodeled dynamics. As shown in Table IV, the average absolute positioning error of the robot is over 4 mm with the Vernier remastering method regardless of reference sensor.…”

Section: B Post-registration Cartesian Accuracymentioning

confidence: 99%

“…Robot positioning errors were reduced to 0.572 mm from over 3 cm. In several works, Y. Liu et al leveraged a low-cost PSD and laser pointer to automate the process of calculating zerooffset parameters through numerical optimization [10], [16]- [18]. Some results showed reduction in positioning errors from over 3 cm to within 0.898 mm.…”

mentioning

confidence: 99%

Efficiently Improving and Quantifying Robot Accuracy In Situ

Wyk

Falco

Cheok

2019

Preprint

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The advancement of simulation-assisted robot programming, automation of high-tolerance assembly operations, and improvement of real-world performance engender a need for positionally accurate robots. Despite tight machining tolerances, good mechanical design, and careful assembly, robotic arms typically exhibit average Cartesian positioning errors of several millimeters. Fortunately, the vast majority of this error can be removed in software by proper calibration of the so-called "zero-offsets" of a robot's joints. This research developed an automated, inexpensive, highly portable, in situ calibration method that fine tunes these kinematic parameters, thereby, improving a robot's average positioning accuracy four-fold throughout its workspace. In particular, a prospective low-cost motion capture system and a benchmark laser tracker were used as reference sensors for robot calibration. Bayesian inference produced optimized zero-offset parameters alongside their uncertainty for data from both reference sensors. Relative and absolute accuracy metrics were proposed and applied for quantifying robot positioning accuracy. Uncertainty analysis of a validated, probabilistic robot model quantified the absolute positioning accuracy throughout its entire workspace. Altogether, three measures of accuracy conclusively revealed multi-fold improvement in the positioning accuracy of the robotic arm. Bayesian inference on motion capture data yielded zero-offsets and accuracy calculations comparable to those derived from laser tracker data, ultimately proving this method's viability towards robot calibration.

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“…Calibration methods utilize an active end-point constraint with the inexpensive device are proposed. In [12], a sphere surface constraint approach with a position sensitive device was presented. Zhu [13] proposed a kinematic self-calibration method by axis constraint with a camera.…”

Section: Introductionmentioning

confidence: 99%

A measurement method for calibrating kinematic parameters of industrial robots with point constraint by a laser displacement sensor

Guo

Song

Tang

et al. 2020

Meas. Sci. Technol.

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This paper proposes a novel calibration method for robot kinematic parameters by constraining a command point. At first, the profile errors derived from measuring the sphere surface by a laser displacement sensor are estimated and analyzed. A three-step measurement procedure is performed around a command point with only one single laser displacement sensor. Then, a kinematic error model including both the robot parameter errors and the errors between the robot base frame and the measurement frame is established. An identification algorithm comprising the least square method and the particle swarm optimization algorithm is developed. Comparison simulations are carried out with the proposed method, a least square method, and the traditional identified method. Experiments show that the estimated compensation results are significant, with the mean reduced from 10.259 mm to 0.845 mm. A verification experiment shows the mean of the relative deviations is decreased from 1.674 mm to 0.538 mm.

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An automated method to calibrate industrial robot kinematic parameters using Spherical Surface constraint approach

Cited by 8 publications

References 9 publications

Novel kinematic model of a SCARA-type robot with bi-directional angular positioning deviation of rotary axes

Novel kinematic model of a SCARA-type robot with bi-directional angular positioning deviation of rotary axes

Efficiently Improving and Quantifying Robot Accuracy In Situ

A measurement method for calibrating kinematic parameters of industrial robots with point constraint by a laser displacement sensor

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