• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.389-399
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• 2014

Purpose: This study was aimed at developing a tractor-driving simulator for the safety training of agricultural tractor operators. Methods: The developed simulator consists of five principal components: mock operator control devices, a data acquisition and processing device, a motion platform, a visual system that displays a computer model of the tractor, a motion platform, and a virtual environment. The control devices of a real tractor cabin were successfully converted into mock operator control devices in which sensors were used for relevant measurements. A 3D computer model of the tractor was also implemented using 3ds Max, tractor dynamics, and the physics of Unity 3D. The visual system consisted of two graphic cards and four monitors for the simultaneous display of the four different sides of a 3D object to the operator. The motion platform was designed with two rotational degrees of freedom to reduce cost, and inverse kinematics was used to calculate the required motor positions and to rotate the platform. The generated virtual environment consisted of roads, traffic signals, buildings, rice paddies, and fields. Results: The effectiveness of the simulator was evaluated by a performance test survey administered to 128 agricultural machinery instructors, 116 of whom considered the simulator as having potential for improving safety training. Conclusions: From the study results, it is concluded that the developed simulator can be effectively used for the safety training of agricultural tractor operators.

• Journal of the Korea Computer Graphics Society
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• v.26 no.4
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• pp.9-15
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• 2020

Having a virtual talking face along with a virtual body increases immersion in VR applications. As virtual reality (VR) techniques develop, various applications are increasing including multi-user social networking and education applications that involve talking avatars. Due to a lack of sensory information for full face and body motion capture in consumer-grade VR, most VR applications do not show a synced talking face and body. We propose a novel method, targeted for VR applications, for talking face synced with audio with an upper-body inverse kinematics. Our system presents a mirrored avatar of a user himself in single-user applications. We implement the mirroring in a single user environment and by visualizing a synced conversational partner in multi-user environment. We found that a realistic talking face avatar is more influential than an un-synced talking avatar or an invisible avatar.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.8 s.197
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• pp.130-137
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• 2007

The optimized prosthetic mass distribution was a controversial problem in the previous studies because they are not supported by empirical evidence. The purpose of the present study was to evaluate the effect of prosthetic mass properties by modeling musculoskeletal system, based on the gait analysis data from two above-knee amputees. The joint torque at hip joint was calculated using inverse dynamic analysis as the mass was changed in knee and foot prosthetic components with the same joint kinematics. The results showed that the peak flexion and abduction torque at the hip joint were 5 Nm and 15 Nm when the mass of the knee component was increased, greater than the peak flexion and abduction torque of the control group at the hip joint, respectively. On the other hand, when the mass of the foot component was increased, the peak flexion and abduction torque at the hip joint were 20 Nm and 15 Nm, greater than the peak flexion and abduction torque of the control, respectively. The hip flexion torque was 4.71-fold greater and 7.92-fold greater than the hip abduction torque for the knee mass increase and the foot mass increase on the average, respectively. Therefore, we could conclude that the effect of foot mass increase was more sensitive than that of knee mass increase for the hip flexion torque. On the contrary, the mass properties of the knee and foot components were not sensitive for the hip abduction torque. In addition, optimized prosthetic mass and appropriate mass distributions were needed to promote efficiency of rehabilitation therapy with consideration of musculoskeletal systems of amputees.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.298-308
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• 2000

In this paper a new two-arm cooperative assembly(or insertion) algorithm is proposed. As a force-guided control method for the cooperative assembly the adaptive accommodation controller is adopted since it does not require any complicated contact state analysis nor depends of the geometrical complexity of the assembly parts. Also the RMRC(resolved motion rate control) method using a relative jacobian is used to solve inverse kinematics for two manipulators. By using the relative jacobian the two cooperative redundant manipulators can be formed as a new single redundant manipulator. Two arms can perform a variety of insertion tasks by using a relative motion between their end effectors. A force/torque sensing model using an approximated penetration depth calculation a, is developed and used to compute a contact force/torque in the graphic assembly simulation . By using the adaptive accommodation controller and the force/torque sensing model both planar and a spatial cooperative assembly tasks have been successfully executed in the graphic simulation. Finally through a cooperative assembly task experiment using a humanoid robot CENTAUR which inserts a spatially bent pin into a hole its feasibility and applicability of the proposed algorithm verified.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.20-32
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• 2010

Previous hardware devices to capture human motion have many limitations; expensive equipment, complexity of manipulation or constraints of human motion. In order to overcome these problems, real-time motion capture algorithms based on computer vision have been actively proposed. This paper presents an efficient analysis method of multiple view images for real-time motion capture. First, we detect the skin color regions of human being, and then correct the image coordinates of the regions by using camera calibration and epipolar geometry. Finally, we track the human body part and capture human motion using kalman filter. Experimental results show that the proposed algorithm can estimate a precise position of the human body.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.175-178
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• 2008

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.162-171
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• 2003

It is difficult to reuse the captured motion data, because the data has a difficulty in editing it. In this paper, a uniform posture mar (UPM) algorithm, one of unsupervised learning neural network is proposed to edit the captured motion data. Because it needs much less computational cost than other motion editing algorithms, it is adequate to apply in teal-time applications. The UPM algorithm prevents from generating an unreal posture in learning phase. It not only makes more realistic motion curves, but also contributes to making more natural motions. Above of all, it complements the weakness of the existing algorithm where the calculation quantity increases in proportion to increase the number of restricted condition to solve the problems of high order articulated body. In this paper, it is shown two applications as a visible the application instance of UPM algorithm. One is a motion transition editing system, the other is a inductive inverse kinematics system. This method could be applied to produce 3D character animation based on key frame method, 3D game, and virtual reality, etc.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.11
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• pp.1243-1248
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• 2011

The purposes of this study were to develop a dynamic model of a human and to investigate the effect of a walker on an elderly subject's motions, such as sit-to-stand (STS) motion and normal gait, by using this model. A human model consisting of 15 segments and 14 joints was developed, embedded in $RecurDyn^{TM}$, and connected through a Simulink$^{(R)}$ interface with collected motion data. The model was validated by comparisons between joint kinematic results from inverse dynamics (Matlab$^{(R)}$-based in-house program) and from $RecurDyn^{TM}$ simulation during walking. The results indicate that the elderly walker induced a longer movement time in walking, such that the speed of joint flexion/extension was slower than that during a normal gait. The results showed that the muscle activities of parts of the ankle and hamstring were altered by use of the elderly walker. The technique used in this study could be very helpful in applications to biomechanical fields.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.121-130
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• 2012

This paper proposes an intuitive real-time robot control system using human body movement. Recently, it has been developed that motion generation for humanoid robots with reflecting human body movement, which is measured by a motion capture. However, in the existing studies about robot control system by human body movement, the detailed structure information of a robot, for example, degrees of freedom, the range of motion and forms, must be examined in order to calculate inverse kinematics. In this study, we have proposed Associative Motion Generation as humanoid robot motion generation method which does not need the detailed structure information. The associative motion generation system is composed of two neural networks: nonlinear principal component analysis and Jordan recurrent neural network, and the associative motion is generated with the following three steps. First, the system learns the correspondence relationship between an indication and a motion using training data. Second, associative values are extracted for associating a new motion from an unfamiliar indication using nonlinear principal component analysis. Last, the robot generates a new motion through calculation by Jordan recurrent neural network using the associative values. In this paper, we propose a real-time humanoid robot control system based on Associative Motion Generation, that enables user to control motion intuitively by human body movement. Through the task processing and subjective evaluation experiments, we confirmed the effective usability and affective evaluations of the proposed system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.505-513
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• 2009

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.