• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.19-26
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• 2019

In this study, we study the development and control of motion of 3D character animation and discuss the development direction of technology. Character animation has been developed as a data-based method and a physics-based method. The animation generation technique based on the keyframe method has been made possible by the development of the hardware technology, and the motion capture device has been used. Various techniques for effectively editing the motion data have appeared. At the same time, animation techniques based on physics have emerged, which realistically generate the motion of the character by physically optimized numerical computation. Recently, animation techniques using machine learning have shown new possibilities for creating characters that can be controlled by the user in real time and are expected to be developed in the future.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.420-425
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• 2008

The technique for synthesizing reactive motion in real-time is important in many applications such as computer games and virtual reality. This paper presents a dynamic motion control technique for creating reactive motions in a physically based character animation system. The leg to move in the next step is chosen using the direction of external disturbance forces and states of human figures and then is lifted though joint PD control. We decide the target position of the foot to balance the body without leg cross. Finally, control mechanism is used to generate reactive motion. The advantage of our method is that it is possible to generate reactive animations without example motions.

• Transactions of the KSME C: Technology and Education
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• v.1 no.2
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• pp.205-210
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• 2013

In this research, we have developed a ski-simulation system based on a physics-based simulation model using Newton's second law of motion. Key parameters of the model, which estimates skier's trajectory, speed and acceleration change due to skier's control on ski plate and posture changes, were derived from a field test study performed on real ski slope. Skier's posture and motion were measured by motion capture system composed of 13 high speed IR camera, and skier's control and pressure distribution on ski plate were measured by acceleration and pressure sensors attached on ski plate and ski boots. Developed ski-simulation model analyzes user's full body and center of mass using a depth camera(Microsoft Kinect) device in real time and provides feedback about force, velocity and acceleration for user. As a result, through the development of interactive ski-simulation motion recognition system, we accumulated experience and skills based on physics models for development of sports simulator.

• Journal of the Korea Computer Graphics Society
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• v.27 no.1
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• pp.9-17
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• 2021

In this paper, we present a simple and fast supervised learning framework based on model predictive control so as to learn motion controllers for a physic-based character to track given example motions. The proposed framework is composed of two components: training data generation and offline learning. Given an example motion, the former component stochastically controls the character motion with an optimal controller while repeatedly updating the controller for tracking the example motion through model predictive control over a time window from the current state of the character to a near future state. The repeated update of the optimal controller and the stochastic control make it possible to effectively explore various states that the character may have while mimicking the example motion and collect useful training data for supervised learning. Once all the training data is generated, the latter component normalizes the data to remove the disparity for magnitude and units inherent in the data and trains an artificial neural network with a simple architecture for a controller. The experimental results for walking and running motions demonstrate how effectively and fast the proposed framework produces physics-based motion controllers.

• Journal of the Korea Computer Graphics Society
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• v.26 no.4
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• pp.1-8
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• 2020

Motion synthesis using physics-based controllers can generate a character animation that interacts naturally with the given environment and other characters. Recently, various methods using deep neural networks have improved the quality of motions generated by physics-based controllers. In this paper, we present a control policy learned by deep reinforcement learning (DRL) that enables Luxo, the mascot character of Pixar animation studio, to run towards a random goal location while imitating a reference motion and maintaining its balance. Instead of directly training our DRL network to make Luxo reach a goal location, we use a reference motion that is generated to keep Luxo animation's jumping style. The reference motion is generated by linearly interpolating predetermined poses, which are defined with Luxo character's each joint angle. By applying our method, we could confirm a better Luxo policy compared to the one without any reference motions.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.133-142
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• 2019

In physics-based character animation, trajectory optimization has been widely adopted for automatic motion synthesis, through the prediction of an optimal sequence of future states of the character based on its system dynamics model. In general, the system dynamics model is neither in a closed form nor differentiable when it handles the contact dynamics between a character and the environment with rigid body collisions. Employing smoothed contact dynamics, researchers have suggested efficient trajectory optimization techniques based on numerical differentiation of the resulting system dynamics. However, the numerical derivative of the system dynamics model could be inaccurate unlike its analytical counterpart, which may affect the stability of trajectory optimization. In this paper, we propose a novel method to derive the closed-form derivative for the system dynamics by properly approximating the contact model. Based on the resulting derivatives of the system dynamics model, we also present a model predictive control (MPC)-based motion synthesis framework to robustly control the motion of a biped character according to on-line user input without any example motion data.

• Progress in Medical Physics
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• v.27 no.3
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• pp.117-124
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• 2016

Intrafractional motion of patients, such as respiratory motion during radiation treatment, is an important issue in image-guided radiotherapy. The accuracy of the radiation treatment decreases as the motion range increases. We developed a control system for a robotic patient immobilization system that enables to reduce the range of tumor motion by compensating the tumor motion. Fusion technology, combining robotics and mechatronics, was developed and applied in this study. First, a small-sized prototype was established for use with an industrial miniature robot. The patient immobilization system consisted of an optical tracking system, a robotic couch, a robot controller, and a control program for managing the system components. A multi speed and position control mechanism with three degrees of freedom was designed. The parameters for operating the control system, such as the coordinate transformation parameters and calibration parameters, were measured and evaluated for a prototype device. After developing the control system using the prototype device, a feasibility test on a full-scale patient immobilization system was performed, using a large industrial robot and couch. The performances of both the prototype device and the realistic device were evaluated using a respiratory motion phantom, for several patterns of respiratory motion. For all patterns of motion, the root mean squared error of the corresponding detected motion trajectories were reduced by more than 40%. The proposed system improves the accuracy of the radiation dose delivered to the target and reduces the unwanted irradiation of normal tissue.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.105-113
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• 2017

This paper presents a novel on-line trajectory optimization framework based on automatic time warping, which performs the time warping of a reference motion while optimizing character motion control. Unlike existing physics-based character animation methods where sampling times for a reference motion are uniform or fixed during optimization in general, our method considers the change of sampling times on top of the dynamics of character motion in the same optimization, which allows the character to effectively respond to external pushes with optimal time warping. In order to do so, we formulate an optimal control problem which takes into account both the full-body dynamics and the change of sampling time for a reference motion, and present a model predictive control framework that produces an optimal control policy for character motion and sampling time by repeatedly solving the problem for a fixed-span time window while shifting it along the time axis. Our experimental results show the robustness of our framework to external perturbations and the effectiveness on rhythmic motion synthesis in accordance with a given piece of background music.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.115-118
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• 2004

Respiratory motion in the thorax and abdomen is an important limiting factor in high-precision radiation therapy. The lung tumor and tumor(pancreas, stomach) in abdomen therefore are internal motion due to breathing. We will perform to measurement of dose distributions for these moving tumors. In preliminary study, we investigated displacement of moving tumor such as liver, lung tumor in abdomen with previously reported papers. With reference data, internal movements of tumor are displayed with phantom and moving control device(MCD), which appear three dimension (3-D) motion such as x, y and z axis. These devices are used to access dose delivered in tumor with and without internal motion. The MCD and phantom were used to evaluate a delivered dose under similar condition, although there are not same internal tumor motion. In future, we will obtain the exact evaluation of dose if improved in programed software of moving control device and measure precise internal motion using image modality such as fluoroscopy, simulator in based on this study.

• Progress in Medical Physics
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• v.18 no.1
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• pp.27-34
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• 2007

Respiration sating radiotherapy technique developed In consideration of the movement of body surface and Internal organs during respiration, is categorized into the method of analyzing the respiratory volume for data processing and that of keeping track of fiducial landmark or dermatologic markers based on radiography. However, since these methods require high-priced equipments for treatment and are used for the specific radiotherapy. Therefore, we should develop new essential method whilst ruling out the possible problems. This study alms to obtain body surface motion by using the couch based computer-controlled motion phantom (CBMP) and US sensor, and to develop respiration gating techniques that can adjust patients' beds by using opposite values of the data obtained. The CBMP made to measure body surface motion is composed of a BS II microprocessor, sensor, host computer and stopping motor etc. And the program to control and operate It was developed. After the CBMP was adjusted by entering random movement data, and the phantom movements were acquired using the sensors, the two data were compared and analyzed. And then, after the movements by respiration were acquired by using a rabbit, the real-time respiration gating techniques were drawn by operating the phantom with the opposite values of the data. The result of analysing the acquisition-correction delay time for the data value shows that the data value coincided within 1% and that the acquistition-correction delay time was obtained real-time $(2.34{\times}10^{-4}sec)$. And the movement was the maximum movement was 6 mm In Z direction, In which the respiratory cycle was 2.9 seconds. This study successfully confirms the clinical application possibility of respiration gating techniques by using a CBWP and sensor.