• Journal of Mechanical Science and Technology
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• v.19 no.10
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• pp.1919-1931
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• 2005

Human joint motion can be kinematically described in three planes, typically the frontal, sagittal, and transverse, and related to experimentally measured data. The selection of reference systems is a prerequisite for accurate kinematic analysis and resulting development of the equations of motion. Moreover, the development of analysis techniques for the minimization of errors, due to skin movement or body deformation, during experiments involving human locomotion is a critically important step, without which accurate results in this type of experiment are an impossibility. The traditional kinematic analysis method is the Angular-based method (ABM), which utilizes the Euler angle or the Bryant angle. However, this analysis method tends to increase cumulative errors due to skin movement. Therefore, the objective of this study was to propose a new kinematic analysis method, Position-based method (PBM), which directly applies position displacement data to represent locomotion. The PBM presented here was designed to minimize cumulative errors via considerations of angle changes and translational motion between markers occurring due to skin movements. In order to verify the efficacy and accuracy of the developed PBM, the mean value of joint dislocation at the knee during one gait cycle and the pattern of three dimensional translation motion of the tibiofemoral joint at the knee, in both flexion and extension, were accessed via ABM and via new method, PBM, with a Local Reference system (LRS) and Segmental Reference system (SRS), and then the data were compared between the two techniques. Our results indicate that the proposed PBM resulted in improved accuracy in terms of motion analysis, as compared to ABM, with the LRS and SRS.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.308-313
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• 2012

Robust tuning rules of the motion profile are proposed to minimize the residual vibration. For asymmetric S-curve profile, tuning rules are analytically formulated using Laplace-domain approach. When the system modeling is known exactly, by placing a single zero of the motion profile on the pole of the system, the residual vibration can be perfectly eliminated under undamped system. However, if there are some amounts of the modeling errors, the residual vibration significantly increases. To track this issue, the robust tuning rules against modeling error are discussed. One of the proposed robust tuning rules is placing the multiple zeros of the motion profile on the pole of the system, and the other is placing the zeros of the motion profile around the pole of the system. Thanks to the proposed robust tuning rules, motion profile becomes more robust to modeling errors while minimizing the residual vibration. By simulation, the effectiveness of the proposed robust tuning rules is verified.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.24-32
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• 2012

Of many approaches to reduce motion analysis errors, the compensation method of anatomical landmarks estimates the position of anatomical landmarks during motion. The method models the position of anatomical landmarks with joint angle or skin marker displacement using the data of the so-called dynamic calibration in which anatomical landmark positions are calibrated in ad hoc motions. Then the anatomical landmark positions are calibrated in target motions using the model. This study applies the compensation methods with joint angle and skin marker displacement to three lower extremity motions (walking, sit-to-stand/stand-to-sit, and step up/down) in ten healthy males and compares their performance. To compare the performance of the methods, two sets of kinematic variables were calculated using different two marker clusters, and the difference was obtained. Results showed that the compensation method with skin marker displacement had less differences by 30~60% compared to without compensation. And, it had significantly less difference in some kinematic variables (7 of 18) by 25~40% compared to the compensation method with joint angle. This study supports that compensation with skin marker displacement reduced the motion analysis STA errors more reliably than with joint angle in lower extremity motion analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.931-938
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• 2008

In this paper, a novel localization algorithm robust to the unmodeled systematic odometry errors is proposed for low-cost non-holonomic mobile robots. It is well known that the most pose estimators using odometry measurements cannot avoid the performance degradation due to the dead-reckoning of systematic odometry errors. As a remedy for this problem, we tty to reflect the wheelbase error in the robot motion model as a parametric uncertainty. Applying the Krein space estimation theory for the discrete-time uncertain nonlinear motion model results in the extended robust Kalman filter. This idea comes from the fact that systematic odometry errors might be regarded as the parametric uncertainties satisfying the sum quadratic constrains (SQCs). The advantage of the proposed methodology is that it has the same recursive structure as the conventional extended Kalman filter, which makes our scheme suitable for real-time applications. Moreover, it guarantees the satisfactoty localization performance even in the presence of wheelbase uncertainty which is hard to model or estimate but often arises from real driving environments. The computer simulations will be given to demonstrate the robustness of the suggested localization algorithm.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.81-85
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• 1991

In this paper, we present a motion compensated video compression method based on both block and object motions. A simplified objectoriented motion parameter is estimated from the block based motion vectors. A decision rule for the global or local MCP modes is established. Simulation results show that the proposed method has lower bit-rates than the BMA based method at the same reconstruction errors.

• Journal of Drive and Control
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• v.20 no.4
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• pp.133-139
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• 2023

A weighing system calculates the bucket's excavation amount of an excavator. Usually, the excavation amount is computed by the excavator's motion equations with sensing data. But these motion equations have computing errors that are induced by assumptions to the linear systems and identification of the equation's parameters. To reduce computing errors, some commercial weighing system incorporates particular motion into the excavation process. This study introduces a linear regression model on an artificial neural network that has fewer predicted errors and doesn't need a particular pose during an excavation. Time serial data were gathered from a 30tons excavator's loading test. Then these data were preprocessed to be adjusted by MPL (Multi Layer Perceptron) or CNN (Convolutional Neural Network) based linear regression models. Each model was trained by changing hyperparameter such as layer or node numbers, drop-out rate, and kernel size. Finally ID-CNN-based linear regression model was selected.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.2
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• pp.55-60
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• 2005

In order to develop the hydrostatic guideways driven by a core less linear motor for ultra precision machine tools, a prototype of guideway is designed and tested. A coreless linear DC motor with a continuous force of 156 N and a laser scale with a resolution of 0.01 ㎛ are used in the system. Experimental analysis on the static stiffness, motion errors, positioning error and its repeatability, micro step response and velocity variation of the guideway are performed. The guideway shows infinite stiffness within 50 N applied load in the feed direction, and by the motion error compensation method using the Active Controlled Capillary, 0.08 ㎛ linear motion error and 0.1 arcsec angular motion error are acquired. The guideway also reveals 0.21 ㎛ positioning error and 0.09 ㎛ repeatability, and it shows stable responses following a 0.01 ㎛ resolution step command. The velocity variation of feeding system is less than 0.6 ％. From these results, it is estimated that the hydrostatic guideway driven by a coreless linear motor is very useful for the ultra precision machine tools.

• Journal of Sensor Science and Technology
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• v.28 no.1
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• pp.30-35
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• 2019

Inertial measurement units (IMUs) are widely used for wearable motion-capturing systems in the fields of biomechanics and robotics. When the IMUs are combined with optical motion sensors (hereafter, OPTs) for their complementary capabilities, it is necessary to align the coordinate system orientations between the IMU and OPT. In this study, we compare the application of two coordinate transformation-based orientation alignment methods between two coordinate systems. The first method (M1) applies angular velocity coordinate transformation, while the other method (M2) applies gyroscopic angle coordinate transformation. In M1 and M2, the angular velocities and angles, respectively, are acquired during random movement for a least-square algorithm to determine the alignment matrix between the two coordinate systems. The performance of each method is evaluated under various conditions according to the type of motion during measurement, number of data points, amount of noise, and the alignment matrix. The results show that M1 is free from drift errors, while drift errors are present in most cases where M2 is applied. Thus, this study indicates that M1 has a far superior performance than M2 for the alignment of IMU and OPT coordinate systems for motion analysis.

• Journal of Mechanical Science and Technology
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• v.20 no.3
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• pp.345-357
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• 2006

By employing the concept of equivalent linkage, this paper presents an analytical method for analyzing the mechanical errors of disk cam mechanisms with a flat-faced follower. The resulting error equations do not really involve the location of the curvature center of the cam profile, and locating the curvature center of the cam profile is not essential. The resulting errors are significantly affected by the pressure angle, and the smaller pressure angle will result in the smaller mechanical error. In the worst case, owing to the joined effects of various design parameters, the accuracy of the follower motion may degrade considerably. For the oscillating follower case, all acceleration error functions have a sudden change at every beginning and at every end of the motion even though the theoretical follower displacement is cycloidal motion.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.5
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• pp.44-51
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• 2008

In this paper, the optimal tuning of a cross-coupled controller linked with the feedforward controller is studied to reduce contouring and tracking errors of a bi-axial servomechanisms by using the previously developed integrated tuning method. The CCC system for an arbitrary curve, which is combined with the feedforward controller, is formulated by a state-space based on a series of linear motion trajectories. An optimal tuning problem is formulated as a nonlinear constrained optimization problem including relevant controller parameters of the servo. To verify the effectiveness of the proposed optimal tuning procedure, linear and circular motion experiments are performed on the xy-table. Experimental results confirm that both tracking and contouring errors are significantly reduced by applying the proposed control and tuning system.