• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.248-255
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• 2020

This paper introduces a Feedback Linearization (FL) controller to eliminate the gyro effect on a quadrotor UAV. In order to control the attitude of the quadrotor, the second model equation was differentiated to the 4-th order to induce the control input to be revealed, and then a new control input was derived based on the attitude transformation equation with a gyro effect. For the initial quick posture control of the quadrotor, the existing yaw control was replaced with a separate controller. The simulation was conducted with an experiment in which FL control to remove the gyro effect was applied to the quadrotor and an experiment without removing the gyro effect, from the experimental results, the maximum error seen in each axial direction of the quadrotor was x = 0.22 m, y = 0.20 m, z = 0.16 m. Through the proposed method, the effect of the FL controller for controlling the gyro effect of the quadrotor was confirmed.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.4
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• pp.11-19
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• 1996

Recently, fuzzy and neural network techniques have been successfully applied to control of complex and ill-defined system in a wide variety of areas, such as robot, water purification, automatic train operation system and automatic container crane operation system, etc. In this paper, we present a neuro-fuzzy controller which unifies both fuzzy logic and multi-layered feedforward neural networks. Fuzzy logic provides a means for converting linguistic control knowledge into control actions. On the other hand, feedforward neural networks provide salient features, such as learning and parallelism. In the proposed neuro-fuzzy controller, the parameters of membership functions in the antecedent part of fuzzy inference rules are identified by using the error backpropagation algorithm as a learning rule, while the coefficients of the linear combination of input variables in the consequent part are determined by using the least square estimation method. Finally, the effectiveness of the proposed controller is verified through computer simulation of an inverted pendulum system.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.273-283
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• 2008

This article describes a cooperative localization technique of multiple robots sharing position information of each robot. In case of conventional methods such as EKF, they need to linearization process. Consequently, they are not able to guarantee that their result is range containing true value. In this paper, we propose a method to merge the data of redundant sensors based on constraints propagation techniques on intervals. The proposed method has a merit guaranteeing true value. Especially, we apply the constraints propagation technique fusing wheel encoders, a gyro, and an inexpensive GPS receiver. In addition, we utilize the correlation between GPS data in common workspace to improve localization performance for multiple robots. Simulation results show that proposed method improve considerably localization performance of multiple robots.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.53-60
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• 2010

We propose a motion planning method for autonomous mobile robots. In order to minimize traveling time, a smooth path and a time optimal velocity profile should be generated under kinematic and dynamic constraints. In this paper, we develop an effective and practical method to generate a good solution with lower computation time. The initial path is obtained from voronoi diagram by Dijkstra's algorithm. Then the path is improved by changing the graph and path simultaneously. We apply the dynamic programming algorithm into the stage of improvement. Simulation results are presented to verify the performance of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.223-233
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• 2008

A new output feedback controller design approach for flexible-joint (FJ) robots via the observer dynamic surface design technique is presented. The proposed approach only requires the feedback of position states. We first design an observer to estimate the link and actuator velocity information. Then, the link position tracking controller using the observer dynamic surface design procedure is developed. Therefore, the proposed controller can be simpler than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop system are uniformly ultimately bounded. Finally, the simulation results of a three-link FJ robot are presented to validate the good position tracking performance of the proposed control system.

• 한국정보교육학회:학술대회논문집
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• 2008.01a
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• pp.245-250
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• 2008

초등학교 정보통신기술 교육에서 새롭게 실시되는 프로그래밍 교육을 위해 로봇 프로그래밍에 대한 관심이 어느 때보다 고조되고 있다. 교육용 로봇을 이용한 프로그래밍교육은 학습자가 로봇을 직접 제작하고 프로그램을 작성하여 실행시키는 과정을 통하여 프로그래밍의 원리뿐만 아니라 학습자의 창의력과 문제해결력 신장에도 많은 도움을 준다. 이러한 로봇 프로그래밍 교육을 활성화시키기 위하여 본 연구에서는 초등학교 아동의 발달 수준에 맞게 게임, 가상체험, 시뮬레이션 기법 등을 적용한 학습 지원시스템을 설계하고자 한다. 이를 통하여 학습자는 고가의 비용을 들이지 않고도 기존의 인터넷 환경에서 접근하여 가상의 로봇을 통하여 재미있고 흥미롭게 프로그래밍기법 및 알고리즘에 대해 쉽게 원리를 배울 수 있는 기회를 제공하고자 한다.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.311-312
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• 2007

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the Maklink graph method. At first, we produce the path of a mobile robot a the static environment. And then we find midpoints of each path using the Maklink graph. Finally the ant colony optimization algorithm is adopted to get a shortest path. In this paper, we prove the performance of the proposed algorithm is better than that of the Dijkstra algorithm through simulation.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.626-633
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• 1995

It is vary hard to identify the fuzzy rules and tune the membership functions of the fuzzy inference in fuzzy systems modeling, We propose a fuzzy neural network model which can automatically identify the fuzzy rules and tune the membership functions of fuzzy inference simultaneously using artificial neural networks, and modify backpropagation algorithm for improving the convergence. The proposed method is verified by the simulation for a robot manipulator.

• Journal of Power Electronics
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• v.13 no.1
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• pp.9-19
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• 2013

In this paper, a ripple input current embedded switched-inductor Z-source inverter (rESL-ZSI) and a continuous input current embedded switched-inductor Z-source inverter (cESL-ZSI) are proposed by inserting two dc sources into the switched-inductor cells. The proposed inverters provide a high boost voltage inversion ability, a lower voltage stress across the active switching devices, a continuous input current and a reduced voltage stress on the capacitors. In addition, they can suppress the startup inrush current, which otherwise might destroy the devices. This paper presents the operating principles, analysis, and simulation results, and compares them to the conventional switched-inductor Z-source inverter. In order to verify the performance of the proposed converters, a laboratory prototype was constructed with 60 $V_{dc}$ input to test both configurations.

• The Transactions of the Korea Information Processing Society
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• v.2 no.3
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• pp.343-353
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• 1995

The path navigation of autonomous guided vehicle(AGV) or autonomous mobile robot(AMR) assumed that the environment was completely known and the obstacles were fixed. So that, in an environment only partly known or not known at all, the previous works were not successful since the path exploration techniques involved in the work were neither directly applicable nor extensible. In order to improve such problems, this paper was adopted the quadtree technique and proposed the algorithm for an optimal path planning autonomously in an environment and proved a validity through a simulation.