• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.6
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• pp.853-860
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• 2014

This paper introduces a Korean rescue robot and presents a whole body kinematic control strategy. The mission of the rescue robot is to move and lift patients or soldiers with impaired mobility in the battlefields, hospitals and hazardous environments. In order for a robot to rescue and assist humans, reliable mobility in various environments, large load carrying capacity, and dextrous manipulability are required. For these objects the robot has variable configuration mobile platform with tracks, dual arm manipulator, and two types of grippers. The electric actuators provide the strength to lift a wounded soldier up to 120 kg using whole body joints. To control the robot with multi degree of freedom, we need to synthesize complex whole-body behaviors, and to manage multiple task primitives systematically. We are to present a whole body kinematic control methodology, and demonstrate its effectiveness through numerical simulations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.2
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• pp.372-379
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• 1998

A new 6 degrees-of-freedom micro stage, based on parallel mechanisms and actuated by using piezoelectric elements, has been developed for the application of micro positioning such as semiconductor manufacturing devices, high precision optical measurement systems, and high accurate machining. The micro stage structure consists of a base platform and an upper platform(stage). The base platform can effectively generates planar motion with yaw motion, while the stage can do vertical motion with roll and pitch motions with respect to the base platform. This separated structure has an advantage of less interference among actuators. The forward and inverse kinematics of the micro stage are discussed. Also, through linearization of kinematic equations about an operating point on the assumption that the configuration of the micro stage remains essentially constant throughout a workspace is performed. To maximize the workspace of the stage relative to fixed frame, an optimal design procedure of geometric parameter is shown. Hardware description and a prototype are presented. The prototype is about 150mm in height and its base platform is approximately 94mm in diameter. The workspace of the prototype is obtained by computer simulation. Kinematic calibration procedure of the micro stage and its results are presented.

• 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 A
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• v.36 no.11
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• pp.1463-1471
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• 2012

In this study, a 3-axis camera system design is proposed for application to an existing 2-axis surveillance robot. A camera-image-based target-tracking algorithm for this robot has also been proposed. The algorithm has been validated using a virtual simulation. In the algorithm, the heading direction vector of the camera system in the mobile surveillance robot is obtained by the position error between the center of the view finder and the center of the object in the camera image. By using the heading direction vector of the camera system, the desired pan and tilt angles for target-tracking and the desired roll angle for the stabilization of the camera image are obtained through inverse kinematics. The algorithm has been validated using a virtual simulation model based on MATLAB and ADAMS by checking the corresponding movement of the robot to the target motion and the virtual image error of the view finder.

• 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.

• 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 the Korea Contents Association
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• v.22 no.3
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• pp.54-61
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• 2022

Ship is a huge system including a variety of pipe arrangements. Pipes are installed according to the design layout, however the end poistion of pipes are not well matched owing to its measurement and construction errors. In this situation, the customized pipe fitting is frequently designed to connect with both pipes, the position of which are manually measured. This paper focused that these two coordinates are measured by point cloud from RGBD sensor and the relative transformation induced by positional and orientational differences is calculated by inverse kinematics in robotics theory. Therefore, the result applies for the methodology of the pipe connection design. The pipe coordinate that is estimated by the matching and the probabilistic RANSAC method will be verified by experiments. The kinematic design parameters are computationally calculated by using the minimum degree of freedom that connects both pipe coordinates.

• 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 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.