• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1629-1632
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• 2003

A technique is presented for generating a compound human motion from its primitive motions obtained by a motion capture system. Some human fundamental motions are modeled in a 3-D way and registered as primitive motions. Because the factorization method is used for the motion capture, calibration of video cameras and connection of the motion in the direction of time is both unnecessary. Employing these motions, various compound human motions are generated by connecting the motions after having applied rotation and parallel transformation to them. Linear interpolation is done at the discontinuous boundary between primitive motions and smooth connection is achieved. Experimental results show satisfactory performance of the proposed technique. The technique may contribute to producing various complicated human motions without much effort using a strict motion capture system.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.1-13
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• 2014

Apart from the physical realism, the implementation of various physical actions of an agent to respond to dynamically changing situations is essential for the design of an agent in a cyber world. To achieve a maximum diversity in actions, we develop a mechanism that allows composite actions to be constructed by reusing a set of primitive motions and enables an agent to instantly react to changes in the ambient states. Specifically we model an agent's body in terms of joints, and a primitive or composite motion is performed in a real time. To implement this mechanism, we produce an animation for basic joint movements and develop a method to construct overall motions out of the primitive motions. These motions can be assembled into a plan by which an agent can achieve a goal. In this manner, diverse actions can be implemented without excessive efforts. This approach has conspicuous advantages when constructing a parallel action, e.g., eating while walking, that is, two or more parallel actions can be naturally merged into a parallel action according to their priority. We implement several composite and parallel actions to demonstrate the viability of our approach.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.4 s.235
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• pp.540-554
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• 2005

This paper presents a motion planning and control method for the dexterous manipulation with a robotic hand. For a given trajectory of an object, a simulation system calculates the necessary joint displacements and contact forces at the fingertip surfaces. These joint displacements and contact forces are the reference inputs to the control loops of the robotic fingers. A task is decomposed into a set of primitive motions, and each primitive motion is executed using the planned output of the simulation system as the reference. Force sensors and dynamic tactile sensors are used to adapt to errors and uncertainties encountered during manipulation. Several experimental results are presented.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.315-316
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• 2007

This paper presents a new methodology to improve movement database for a humanoid robot. The database is initially full of human motions so that the kinetics characteristics of human movement are immanent in it. then, the database is updated to the pseudo-optimal motions for the humanoid robot to perform more natural motions, which contain the kinetics characteristics of robot. for this, we use the evolutionary algorithm. the methodology consists of two processes : (1) the offline imitation learning of human movement and (2) the online generation of natural motion. The offline process improve the initial human motion database using the evolutionary algorithm and inverse dynamics-based optimization. The optimization procedure generate new motions using the movement primitive database, minimizing the joint torque. This learning process produces a new database that can endow the humanoid robot with natural motions, which requires minimal torques. In online process, using the linear combination of the motion primitive in this updated database, the humanoid robot can generate the natural motions in real time. The proposed framework gives a systematic methodology for a humanoid robot to learn natural motions from human motions considering dynamics of the robot. The experiment of catching a ball thrown by a man is performed to show the feasibility of the proposed framework.

• International Journal of Contents
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• v.15 no.4
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• pp.16-26
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• 2019

The efficient implementation of various physical actions of agents to respond to dynamically changing situations is essential for the simulation of realistic agents and activities in a cyber world. To achieve a maximum diversity of actions and immediate responsiveness to abrupt changes in situations, we have developed an animation technique in which complex actions are recursively constructed by reusing a set of primitive motions, and agents are designed to react in real-time to abrupt ambient changes by computationally satisfying kinematic constraints on body parts with respect to their goals. Our reusing scheme is extended to visualize the procedure of realistic intricate situations involving many concurring events. Our approach based on motion reuse and recursive assembly has clear advantages in motion variability and action diversity with respect to authoring scalability and motion responsiveness compared to conventional monolithic (static) animation techniques. This diversity also serves to accommodate the characteristic unpredictability of events concurring in a situation due to inherent non-determinism of associated conditions. To demonstrate the viability of our approach, we implement several composite and parallel actions in a dynamically changing example situation involving events that were originally independent until coincidentally inter-coupled therein.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1038-1046
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• 2008

This paper presents a framework to generate human-like movements of a humanoid in real time using the movement primitive database of a human. The framework consists of two processes: 1) the offline motion imitation learning based on an Evolutionary Algorithm and 2) the online motion generation of a humanoid using the database updated bγ the motion imitation teaming. For the offline process, the initial database contains the kinetic characteristics of a human, since it is full of human's captured motions. The database then develops through the proposed framework of motion teaming based on an Evolutionary Algorithm, having the kinetic characteristics of a humanoid in aspect of minimal torque or joint jerk. The humanoid generates human-like movements far a given purpose in real time by linearly interpolating the primitive motions in the developed database. The movement of catching a ball was examined in simulation.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.238-246
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• 2001

We have developed the sign-language synthesis system, which can be applied for intelligent terminal equipments, for the purpose of communications between normal people and the hearing-impaired. In the system, we generate the behavior of the sign-language words using CG animation based on Motion-Primitives of the motion observed of each legion of the body in the generation of words, the conventional system was difficult to control the shape of hands and the motions of hands and shoulder, requiring lots of time for the processing. Also it is a big problem to make a large database of sign-language, because it requires over 5,000 words to translate the sign-language. Therefore, in this paper, we propose the new system that is easy to construct the database by using Motion-Primitives, which can make paths of various motions more smooth than conventional systems. We have tested 100 words of the sign-language against the hearing-impaired with the proposed system. As the result of testing by the proposed system, we have earned a good recognition rate with 82%. On the other hand, we had earned the recognition ratio with 76% by using the former system.

• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.60-67
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• 1997

CAD systems offer a variety of techniques for designing and rendering models of static 3D objects and even of mechanisms, but relatively few tools exist for interactively specifying arbitrary movements of rigid bodies through space. Such tools are essential, not only for artistic animation, but also, for planning and demonstrating assembly and disassembly procedure of manufactured products. A rigid body motion is a continuous mapping from the time domain to a set of positions. To relieve the designers from the burden of specifying this mapping in abstract mathematical terms, combinations of simple rigid motion primitives, such as linear translations or constant axis rotations, are often used. These simple motions are planar and thus ill-suited for approximating arbitrary motions in 3D-space. Instead, we propose the screw motion primitive, a special combination of linear translations and constant axis rotations, which has a simple geometric representation that can be automatically and unambiguously computed from the starting and ending positions of the moving body. Although, any two positions may be interpolated by an infinity of motions, we chose the screw motion for its relative generality and its computational advantages. The paper covers original algorithms for computing the screw motions from interpolated positions and envelopes of swept regions to predict collisions.

• The Journal of Korea Robotics Society
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• v.8 no.1
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• pp.1-7
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• 2013

Body gesture Recognition has been one of the interested research field for Human-Robot Interaction(HRI). Most of the conventional body gesture recognition algorithms used Hidden Markov Model(HMM) for modeling gestures which have spatio-temporal variabilities. However, HMM-based algorithms have difficulties excluding meaningless gestures. Besides, it is necessary for conventional body gesture recognition algorithms to perform gesture segmentation first, then sends the extracted gesture to the HMM for gesture recognition. This separated system causes time delay between two continuing gestures to be recognized, and it makes the system inappropriate for continuous gesture recognition. To overcome these two limitations, this paper suggests primitive body model encoding, which performs spatio/temporal quantization of motions from human body model and encodes them into predefined primitive codes for each link of a body model, and Selective/Asynchronous Input-Parallel State machine(SAI-PSM) for multiple-simultaneous gesture recognition. The experimental results showed that the proposed gesture recognition system using primitive body model encoding and SAI-PSM can exclude meaningless gestures well from the continuous body model data, while performing multiple-simultaneous gesture recognition without losing recognition rates compared to the previous HMM-based work.

• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.9-20
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• 2011

In this paper, we attempt to realize the diversity of human actions in a virtual world in terms of the basic actions. We utilize the comprehensive knowledge structure of ontology to organize the human actions into an action hierarchy, each action being the root action of its associated hierarchy of specialized actions. Each basic action is implemented by composing the primitive motions and each basic action in turn by reusing those basic actions. Our approach to the development of these actions is focused more on their diversity and brevity than on their visual realism. Based on this design we develop a method to grasp virtual humans' characteristics and reflect those characteristics on their respective action patterns. We also present a mechanism for the agents to adapt their motions to diverse qualitative changes in environment. We apply these methods to such basic actions as walk, run and throw to demonstrate their viability.