Error analysis of a parallel mechanism considering link stiffness and joint clearances

Lim, Seung Reung; Kang, Kyungwoo; Park, Sungchul; Choi, Woo Chun; Song, Jae Bok; Hong, Daehie; Shim, Jae Kyung

doi:10.1007/bf02939339

Cited by 13 publications

(9 citation statements)

References 4 publications

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“…( ), (8) where q is the generalized coordinate column matrix. M(q(t)) denotes the inertia matrix of the robot manipulator.…”

Section: Fig 2 Friction Coefficient and Slip Velocitymentioning

confidence: 99%

“…A general probability density function of the endpoint of planar robots with joint clearance was established to derive the distribution functions for any position tolerance zone and any joint distribution type [7]. Some errors arising from link stiffness and clearances were considered to predict the accuracy of the parallel devices [8]. By considering the positional and directional errors of the robot hand and the manufacturing cost, the optimal allocation of joint tolerances was investigated.…”

Section: Introductionmentioning

confidence: 99%

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Effects of Joint Clearance on the Motion Accuracy of Robotic Manipulators

2018

SV-JME

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Accuracy is one of the key features that improves the quality of robotic manipulators for many industrial and medical applications. Even with an accurate design and manufacturing process, clearance problems in joints cannot be eliminated in articulated systems. This leads to a loss of accuracy in robotic manipulation. In this study, the effects of joint clearance in a robotic system are investigated. The need for the trajectory of end effector is considered to analyse the motion sensitivity. The kinematics and dynamics of a six-DOF robot with joint clearance are evaluated relative to a robot without joint clearance. Different scenarios for clearance values and working periods are performed to fulfil the required motion task. A neural model is also used to predict the trajectory deviations during the working process. The results show that clearance has a significant role in the motion sensitivity of robotic manipulations. Trajectory errors can also be determined by using a dynamic neural predictor with suitable input variables.

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“…( ), (8) where q is the generalized coordinate column matrix. M(q(t)) denotes the inertia matrix of the robot manipulator.…”

Section: Fig 2 Friction Coefficient and Slip Velocitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effects of Joint Clearance on the Motion Accuracy of Robotic Manipulators

2018

SV-JME

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“…For the aforementioned reasons, other factors are gradually considered in the stiffness model, such as limb deformation, [6][7][8] joint clearance, [9][10][11] joint contact deformation, [12][13][14][15] and others. 16 However, most models are a combination of two or three factors, such as actuator stiffness and limb deformation, 17,18 actuator stiffness and joint clearances, 19 joint clearances and limb deformation, 20,21 and others. 22,23 It can be seen that the previous studies focused on the partial factors, and there are few complete models.…”

Section: Introductionmentioning

confidence: 99%

Approximate Stiffness Modelling and Stiffness Defect Identification for a Heavy-load Parallel Manipulator

Fan¹,

Fan²

2019

Robotica

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SummaryWhen using parallel manipulators as machine tools, their stiffness is an important factor in the quality of the produced products. This paper presents an overall approximate stiffness model for a heavy-load parallel manipulator, which considers the effects of actuator stiffness, joint clearance, joint contact deformation, and limb deformation. Based on the principle of virtual work and the introduced modified parameters, the proposed overall compliance matrix successfully takes four factors into a unified expression. To obtain the overall compliance matrix, the approximate stiffness models of the joint clearance, joint contact deformation, and limb deformation are given. In addition, by combining the statistical simulation including the random uncertainties and the proposed approximate stiffness models as the basis of the magnitudes for each random variable, an approach based on the expected trajectory and external load is also proposed for stiffness defect identification such that the estimation is more accurate and reliable. Finally, a numerical example of the 1PU+3UPS parallel manipulator and a discussion are presented to demonstrate the practicability of the proposed stiffness model and defect identification approach. After modifying the structure parameters of the defective components, the prototype experiences a significant stiffness improvement.

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“…This measurement system, which consists of three linear sensors and directly senses the final position of the platform, can be considered another parallel mechanism. In order to achieve the high position accuracy of a machine tool, positioning stage and robot, it is important to estimate the error of its end effector due to the uncertainties in parts [8]. One method for estimating and/or eliminating the error of the end effector that comes from uncertainties in machine components is kinematic calibration.…”

Section: Introductionmentioning

confidence: 99%

Development and kinematic calibration for measurement structure of a micro parallel mechanism platform

2008

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This paper presents a micro-positioning platform based on a unique parallel mechanism developed by the authors. The platform has a meso-scale rectangular shape whose size is 20 x 23 mm. The stroke is 5 mm for both the x-and yaxes and 100 degrees for the -axis. The platform is actuated by three sets of dual stage linear actuators: a linear motor for rough positioning and a piezo actuator for fine positioning. The developed micro-positioning platform has a measurement system that consists of three linear sensors. The position and orientation values of the movable platform can be measured directly and used in a feedback control system. Selecting 18 kinematic error parameters of a measurement system (feedback control system), a two-stage kinematic calibration method is proposed. Constant error parameters are found in the first stage and variable error parameters are found in the second stage of kinematic calibration. After kinematic calibration the position error is reduced to within 0.5 and error reduction rate is over 90%.

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Error analysis of a parallel mechanism considering link stiffness and joint clearances

Cited by 13 publications

References 4 publications

Effects of Joint Clearance on the Motion Accuracy of Robotic Manipulators

Effects of Joint Clearance on the Motion Accuracy of Robotic Manipulators

Approximate Stiffness Modelling and Stiffness Defect Identification for a Heavy-load Parallel Manipulator

Development and kinematic calibration for measurement structure of a micro parallel mechanism platform

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