• Journal of the Ergonomics Society of Korea
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• v.25 no.2
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• pp.51-62
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• 2006

In assessing risks related to working posture, pictures of postures are taken from various directions, which can be a source of observation error. Joint postures of the neck, lower back, knee, shoulder, and elbow were taken from 7 different viewing angles and 19 observers estimated joint angles by observing the pictures in 2-dimensional display. The joint angles were also measured using an optoelectronic motion measurement system. The estimation error increased as the viewing angle varies from the right side of the human body, but the patterns differ according to which joint angles were being observed. Guidelines to increase the validity of observation of joint angles were presented based on the results. In general, it is recommended to maintain the viewing angle within 20 degrees from the right side of the human body, while different ranges of viewing angle are recommended for each joint angle.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.9
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• pp.986-994
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• 2012

This paper is concerned with the application of the vision control algorithm with weighting matrix in robot point placement task. The proposed vision control algorithm involves four models, which are the robot kinematic model, vision system model, the parameter estimation scheme and robot joint angle estimation scheme. This proposed algorithm is to make the robot move actively, even if relative position between camera and robot, and camera's focal length are unknown. The parameter estimation scheme and joint angle estimation scheme in this proposed algorithm have form of nonlinear equation. In particular, the joint angle estimation model includes several restrictive conditions. For this study, the weighting matrix which gave various weighting near the target was applied to the parameter estimation scheme. Then, this study is to investigate how this change of the weighting matrix will affect the presented vision control algorithm. Finally, the effect of the weighting matrix of robot vision control algorithm is demonstrated experimentally by performing the robot point placement.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.169-172
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• 2019

Frequency-modulated continuous wave(FMCW) radars with array antennas are widely used because of their light weight and relatively high resolution. A usual approach for the joint range and angle estimation of a target using an array FMCW radar is to create a range-angle matrix with the deramped received signal, and subsequently apply two-dimensional(2D) frequency estimation methods such as 2D fast Fourier transform on the range-angle matrix. However, such frequency estimation approaches cause bias errors since the frequencies in the range-angle matrix are not independent. Therefore, we propose a new maximum likelihood-based algorithm for joint range and angle estimation of targets using array FMCW radar, and demonstrate that the proposed algorithm achieves the Cram?r-Rao bounds, both for range as well as angle estimation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.15-25
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• 2010

The objective of this study is to investigate the optimal arrangement of cameras used for the robot's vision control scheme. The used robot's vision control scheme involves two estimation models, which are the parameter estimation and robot's joint angle estimation models. In order to perform this study, robot's working region is divided into three work spaces such as left, central and right spaces. Also, cameras are positioned on circular arcs with radius of 1.5m, 2.0m and 2.5m. Seven cameras are placed on each circular arc. For the experiment, nine cases of camera arrangement are selected in each robot's work space, and each case uses three cameras. Six parameters are estimated for each camera using the developed parameter estimation model in order to show the suitability of the vision system model in nine cases of each robot's work space. Finally, the robot's joint angles are estimated using the joint angle estimation model according to the arrangement of cameras for robot's point-position control. Thus, the effect of camera arrangement used for the robot's vision control scheme is shown for robot's point-position control experimentally.

• ETRI Journal
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• v.43 no.1
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• pp.120-132
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• 2021

A frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar employs a small frequency increment across transmit elements to produce an angle-range-dependent beampattern for target angle and range detection. The joint angle and range estimation problem is a trilinear model. The traditional trilinear alternating least square (TALS) algorithm involves high computational load due to excessive iterations. We propose a fast-convergence trilinear decomposition (FC-TD) algorithm to jointly estimate FDA-MIMO radar target angle and range. We first use a propagator method to obtain coarse angle and range estimates in the data domain. Next, the coarse estimates are used as initialized parameters instead of the traditional TALS algorithm random initialization to reduce iterations and accelerate convergence. Finally, fine angle and range estimates are derived and automatically paired. Compared to the traditional TALS algorithm, the proposed FC-TD algorithm has lower computational complexity with no estimation performance degradation. Moreover, Cramer-Rao bounds are presented and simulation results are provided to validate the proposed FC-TD algorithm effectiveness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5860-5876
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• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

• Journal of Industrial Technology
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• v.28 no.A
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• pp.167-176
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• 2008

Recently, lots of studies are performed in developing of active orthosis. Exact and simple muscle force estimation is important in developing orthosis which assists muscle force for disabled people or physical laborers. Hill-type muscle model dynamics is common method for estimation of muscle forces. In Hill-type muscle model, we must know muscle length and moment arm which largely affect muscle force. And several methods are proposed to estimate muscle length and moment arm using joint angle. In this study, we compared estimation results of those method with data from body model of opensim to find which method is exact for estimation of muscle length and moment arm.

• Proceedings of the ESK Conference
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• 1994.04a
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• pp.115-123
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• 1994

A man model can be used as an effective tool to design ergomonically sound products and workplaces, and subsequently evaluate them properly. For a man model to be truly useful, it must be integrated with a posture prediction model which should be capable of representing the human arm reach posture in the context of equipments and workspaces. Since the human movement possesses redundant degrees of freedom, accurate representation or prediction of human movemtn was known to be a difficult problem. To solve this redundancy problem, the psychophysical cost function can predict the arm reach posture accurately. But the joint discomfort that human feels at the joint can not be predicted since the effects of external factors on the joint discomfort is not known. In this study a psychophysical experi- ment using the magnitude estimation technique was performed to evaluate the effects of external factors such as joint, joint angle and Perceived Exertion Ratio on the joint discomfort. Results showed that the joint discomfort increased as the Perceived Exertion Ratio increased, but the relation is not linear and was affected not only by the joint but also by the joint angle for the same Perceived Exertion Ratio. The interaction effect of the joint and the joint angle was also significant. From the results it is needed to develope the cost function which can predict the joint discomfort considering the joint, joint angle and external load.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2879-2890
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• 2020

In this paper, we study the estimation of angle, range and polarization parameters of a bistatic polarization sensitive frequency diverse array multiple-input multiple-output (PSFDA-MIMO) radar system. The application of polarization sensitive array in receiver is explored. A signal model of bistatic PSFDA-MIMO radar system is established. In order to utilize the multi-dimensional structure of array signals, the matched filtering radar data can be represented by a third-order tensor model. A joint estimation of the direction-of-departure (DOD), direction-of-arrival (DOA), range and polarization parameters based on parallel factor (PARAFAC) algorithm is proposed. The proposed algorithm does not need to search spectral peaks and singular value decomposition, and can obtain automatic pairing estimation. The method was compared with the existing methods, and the results show that the performance of the method is better. Therefore, the accuracy of the parameter estimation is further improved.

• Journal of Biomedical Engineering Research
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• v.29 no.3
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• pp.222-230
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• 2008

This paper introduces a method of estimating the knee joint moment developed during MVC. By combining the Hill-type muscle model and analytic results on moment arm and musculotendon length change as a function of hip and knee joint angle, the knee joint moment at a specific knee joint angle during MVC is determined. Many differences between the estimated results and the experimental data are noted. It is believed that these differences originate from inaccurate information on the muscle-tendon parameters. The establishment of exact values for the subject's muscle parameters is almost impossible task. However, sensitivity analysis shows that the tendon slack length is the most critical parameter when applying the Hill-type muscle model. The effect of a change of this parameter on the muscle length force relationship is analyzed in detail.