• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.80-83
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• 2001

이족로봇이 stand-alone 형태를 가지기 위해서는 기계적인 구조가 중요할 뿐만 아니라 하드웨어시스템이 간결하게 잘 설계되어야 한다. 이렇게 하드웨어시스템이 가볍고 간결하여 설계되어야 쉽게 로봇에 장착할 수가 있다. 본 논문에서는 FPGA(Field Programmable Gate Array)를 이용해 모터 제어기를 구성해서 이족로봇을 설계하는 방법을 다루고자 한다. 본 논문에서 구성하는 하드웨어 시스템은 메인 CPU로 AM186ES를 사용하며 FPGA는 Altera사의 FLEX EPF10K20TC144-3을 사용하였다. 이와 같이 FPGA를 사용하는 하드웨어시스템은 기본적으로 VHDL언어를 사용하여 유연하게 하드웨어를 구성 할 수 있으며, 이족로봇의 여러 가지 보행 알고리즘에 능동적으로 대처할 수 있다. 뿐만 아니라 하드웨어가 간단해 지면서 가볍고 전력소모가 적으며 신뢰성 있는 시스템을 구축할 수 있다.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.275-281
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• 2007

This paper presents a motion planning strategy for legged robots using locomotion primitives in the complex 3D environments. First, we define configuration, motion primitives and locomotion primitives for legged robots. A hierarchical motion planning method based on a combination of 2.5 dimensional maps of the 3D workspace is proposed. A global navigation map is obtained using 2.5 dimensional maps such as an obstacle height map, a passage map, and a gradient map of obstacles to distinguish obstacles. A high-level path planner finds a global path from a 2D navigation map. A mid-level planner creates sub-goals that help the legged robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local obstacle map that describes the edge or border of the obstacles is used to find the sub-goals along the global path. A low-level planner searches for a feasible sequence of locomotion primitives between sub-goals. We use heuristic algorithm in local motion planner. The proposed planning method is verified by both locomotion and soccer experiments on a small biped robot in a cluttered environment. Experiment results show an improvement in motion stability.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.236-241
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• 2008

This paper presents a method to recognize the plane regions for movement of walking robots. When the autonomous agencies using stereo camera or laser scanning sensor is under unknown 3D environment, the mobile agency has to detect the plane regions to decide the moving direction and perform the given tasks. In this paper, we propose a very fast method for plane detection using normal vector of a triangle by 3 vertices defined on a small circular region. To reduce the effect of noises and outliers, the triangle rotates with respect to the center position of the circular region and generates a series of triangles with different normal vectors based on different three points on the boundary of the circular region. The vectors for several triangles are normalized and then median direction of the normal vectors is used to test the planarity of the circular region. The method is very fast and we prove the performance of algorithm for real range data obtained from a stereo camera system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.10
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• pp.89-94
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• 2012

This research is to apply the control of neuron networks for the real-time walking control of Multi-articulated robot. Multi-articulated robot is expressed with a complicated mathematical model on account of the mechanic, electric non-linearity which each articulation of mechanism has, and includes an unstable factor in time of walking control. If such a complex expression is included in control operation, it leads to the disadvantage that operation time is lengthened. Thus, if the rapid change of the load or the disturbance is given, it is difficult to fulfill the control of desired performance. This paper proposes a new mode to implement a neural network controller by installing a real object for controlling and an algorithm for this, which can replace the existing method of implementing a neural network controller by utilizing activation function at the output node. The proposed control algorithm generated control signs corresponding to the non-linearity of Multi-articulated robot, which could generate desired motion in real time.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.124-129
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• 2013

Hexapod walking robots are superior to biped or quadruped ones in terms of walking stability. Therefore hexapod robots have the advantage in performing intelligent tasks based on walking stability. In this paper, we propose a hexapod robot that has one fore leg, one hind leg, two left legs, and two right legs and can perform various intelligent tasks. We build the robot by using 26 motors and implement a controller which consists of a host PC, a DSP main controller, an AVR auxiliary controller, and smart phone/pad. We show by several experiments that the implemented robot can perform various intelligent tasks such as uneven surface walking, tracking and kicking a ball, remote control and 3D monitoring by using data obtained from stereo camera, infrared sensors, ultra sound sensors, and contact sensors.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.5
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• pp.142-149
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• 2009

This paper proposes and demonstrates novel flexible contact force sensing devices for 3-dimensional force measurement. To realize the sensor, polyimide and polydimethylsiloxane are used as a substrate, which makes it flexible. Thin-film metal strain gauges, which are incorporated into the polymer, are used for measuring the three-dimensional contact forces. The force sensor characteristics are evaluated against normal and shear load. The fabricated force sensor can measure normal loads up to 4N. The sensor output signals are saturated against load over 4N. Shear loads can be detected by different voltage drops in strain gauges. The device has no fragile structures; therefore, it can be used as a ground reaction force sensor for balance control in humanoid robots. Four force sensors are assembled and placed in the four corners of the robot's sole. By increasing bump dimensions, the force sensor can measure load up to 20N. When loads are exerted on the sole, the ground reaction force can be measured by these four sensors. The measured forces can be used in the balance control of biped locomotion system.

• Journal of the Korea Computer Graphics Society
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• v.5 no.2
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• pp.33-41
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• 1999

This paper presents a new algorithm about motion adjustment for dynamic balance. It adjusts an unbalanced motion to an balanced motion while preserving the nuance of original motion. We solve dynamic balancing problem using the zero moment point (ZMP) which is often used for controlling the balance of biped robot. Our algorithm is consists of four steps. First, it fits joint angle data to spline curves for reducing noise. Second, the algorithm analyzes the ZMP trajectory so that it can detects the dynamically-unbalanced duration. Third, the algorithm project the ZMP trajectory into the supporting area if the trajectory deviates from the area. Finally, the algorithm produces the balanced motion that satisfies the new ZMP trajectory. In this step, the constrained optimization method is used so that the new motion keeps the original motion characteristics as much as possible. We make several experiments in order to prove that our algorithm is useful to add physical realism to a kinematically edited motion.

• 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.

• Journal of Korea Entertainment Industry Association
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• v.8 no.2
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• pp.283-297
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• 2014

The future of human life is expected to be innovative by increasing social, economic, political and personal, including all areas of life across the multi-disciplinary skills. Particularly, in the field of robotics and next-generation games with robots, by multidisciplinary contributions and interaction, convergence between technology is expected to accelerate more and more. The purpose of this study is that by new interface model beyond the technical limitations of the "human-robot interface technology," until now and time and spatial constraints and through fusion of various modalities which existing human-robot interface technologies can't have, the research of more reliable and easy free "human-robot interface technology". This is the research of robot game system which develop and utilizing real time synchronization engine linking between biped humanoid robot and the behavior of the position value of mobile device screen's 3D content (contents), robot (virtual robots), the wireless protocol for sending and receiving (Protocol) mutual information and development of a teaching program of "Direct Teaching & Play" by the study for effective teaching.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.3
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• pp.68-76
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Thus, in this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm(RVEGA) was presented for stabilization of an IP system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. And the proposed ENNC was implemented successfully on the ADA-2310 data acquisition board and the 80586 microprocessor in order to stabilize the IP system. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.