Calibration Of Parallel Manipulators Research Articles

Enhancing Kinematic Calibration Accuracy for Parallel Manipulators Based on Truncated Total Least-Square Regularization

Abstract This article proposes a novel kinematic calibration approach to address the ill-conditioned identification matrix problem and enhance the accuracy of parallel manipulators (PMs). The kinematic calibration approach applies the truncated total least-square (T-TLS) regularization method to the inverse kinematic calibration of PMs and does not have the unit inconsistency issue and configuration selection issue. The performance of the T-TLS method in the inverse kinematic calibration of PMs that have the ill-conditioned identification matrix problem is compared to that of classical regularization methods, including the truncated singular value decomposition (TSVD) method and Tikhonov method, in simulations. Then, the kinematic calibration approach is applied to a 3-PSS/S spherical PM prototype in the real world. For the 3-PSS/S spherical PM prototype, the kinematic calibration approach can reduce the absolute angular errors of the end-effector from over 1.0 deg before calibration to less than 0.1 deg after calibration.

Kinematic Calibration of a 6-DoF Parallel Manipulator With Random and Less Measurements

Parallel manipulator (PM) embraces more kinematic errors than serial mechanism. The substantial errors in PM usually demand more measurements, which leads to low efficiency and affects the accuracy of identification due to the ill-conditioning problem. Having realized this common problem in the kinematic calibration of PMs, we carried out a finite and instantaneous screw (FIS)-based kinematic calibration on a 6- <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</u> UHU PM before application to fracture reduction. <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</u> , U, and H denote actuated revolute joint, universal joint, and helical joint, respectively. The error model is built by the error mapping of serial chains in the FIS framework. Instead of devoting to the measurement planning for more precise identification, the identifiability of kinematic errors is thoroughly analyzed. Redundant errors are categorized as the ones within limb and among limbs. A minimal identification model is thus defined and an error conversion method is proposed for compensation. Calibration experiments show that the FIS method has an improved accuracy of the 6- <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</u> UHU PM at least one magnitude higher than the precision demand, i.e., mean position and orientation errors 0.0574 mm and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5.1197\,\,{\times }\,\, 10^{-4}$ </tex-math></inline-formula> rad after calibration. Compared with the conventional closed-loop vector (CLV) equation method, the accuracy improvement of FIS method is higher. In addition, comparisons with the commonly used configuration selection methods indicate that our method allows random and a smaller number of measurements and can reach satisfactory accuracy.

Kinematic Calibration of Parallel Manipulator for Semi-physical Simulation System

Kinematic Calibration of Parallel Manipulator for Semi-physical Simulation System

FIXTURELESS CALIBRATION OF PARALLEL MANIPULATORS

Identification objective functions considering end effector pose errors and branch end distance errors for the calibration of parallel manipulators are discussed. Based on the elimination of the need for fixturing devices, branch end distance error based objectives are demonstrated preferred. Kinematic calibration models that include device geometric parameters, for the RSI 6 degree of freedom hand controller, are introduced. Calibrations considering more complete models are demonstrated to yield improved calibrations in comparison to models considering only original non-zero length and angle parameters and potentiometer parameters. The complete calibration model is found to return error values within a range of the same order of magnitude as branch end distance fluctuation due to joint displacement sensors’ noise. To achieve higher precision, it is concluded that noise-free joint displacement sensing and accurate passive spherical branch end joints are required.