• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.120.5-120
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• 2001

This paper introduces an Adapative Goal Pertubation Method(AGPM) for mobile robots which can move safely without being locked in a trap situation. AGPM is a modified method of VFH(Vector Field Histrogram) that Borenstein has proposed. AGPM consists of Avoid-Trap-Mode, Escape-Trap-Mode and Check-Trap-Mode. Some results of the mobile robot that have 8 ultrasonic sensors are shown through simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.91.3-91
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• 2001

A sensor fusion scheme for mobile robot environment recognition that incorporates range data and contour data is proposed. Ultrasonic sensor provides coarse spatial description but guarantees open space with no obstacle within sonic cone with relatively high belief. Laser structured light system provides detailed contour description of environment but prone to light noise and is easily affected by surface reflectivity. Overall fusion process is composed of two stages: Noise elimination and belief updates. Dempster Shafer´s evidential reasoning is applied at each stage. Open space estimation from sonar range measurements brings elimination of noisy lines from laser sensor. Comparing actual sonar data to the simulated sonar data enables ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.155.5-155
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• 2001

The robust predictive control law which use the bound estimation is proposed for uncertain robot manipulators. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about model, it´s an important tend to design a robust control law that will guarantee the desired performance of the manipulator under uncertain elements. In the preceeding work, the robust predictive control law was proposed. In this work, we propose a class of robust predictive control of manipulators with the bound estimate technique and fe stability based on Lyapunov function is presented.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.149.5-149
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent´s dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless ...

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.92.3-92
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• 2002

A lot of localization algorithms have been developed in order to achieve autonomous navigation. However, most of localization algorithms are restricted to certain conditions. In this paper, Monte Carlo localization scheme with a map-matching algorithm is suggested as a robust localization method for the Public Service Robot to accomplish its tasks autonomously. Monte Carlo localization can be applied to local, global and kidnapping localization problems. A range image based measure function and a geometric pattern matching measure function are applied for map matching algorithm. This map matching method can be applied to both polygonal environments and un-polygonal environments and achieves...

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.92.2-92
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• 2002

Building autonomous robots have been a central objective of research in artificial intelligence. The development of techniques for autonomous navigation in real environment consist one of the main tendencies of the current researches about Robotics. An important problem in autonomous navigation is the necessity of dealing with a great amount of uncertainties inherent to the real environments. The paraconsistent logic has characteristics that make it become an adequate tool to solve this problem. In this work, it is proposed a technique of mapping the real world in the navigation of an autonomous robot using the paraconsistent logic.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.33.4-33
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• 2002

Recently, number of navigation system using GPS and other complementary sensor has been developed to offer high-position accuracy. In this paper, we developed navigation system for mobile robot integrating GPS and DR sensor information provided by fiber optic gyroscopes and encoder information. In the case of short-term applications, integrating this encoder and gyroscope through Kalman filter reliable positioning can be obtained. And for the long-term applications we developed GPS/DR Integration algorithm using Kalman filter

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.105.2-105
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• 2002

$\textbullet$ Statically stable walk with COG(center of gravity) $\textbullet$ Dynamically stable walk with ZMP(zero moment point) $\textbullet$ Dynamically adaptational stable walk with FRI(foot ratation indicator) $\textbullet$ Simplified inverted pendulum model approach $\textbullet$ Analysis posture of biped's foot as passive joint $\textbullet$ Stability compensation method of FRI against falling down $\textbullet$ Simulation of ZMP and FRI to real biped robot IWR-III

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.105.3-105
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• 2002

The Field Robot means the machinery applied for outdoor tasks in construction, agriculture, and undersea etc. In this study, to robotize the hydraulic excavator that is mostly used in construction working. we developed an interfacing hardware units of stroke sensing cylinder using magnetic sensor and estimated its performance. It is illustrated by experiment that the proposed control system by stroke sensing cylinder gives good performances in the position control.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.106.2-106
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• 2002

$\textbullet$ Contents 1. Introduction $\textbullet$ Contents 2. System Configuration $\textbullet$ Contents 3. Robot Kinematics $\textbullet$ Contents 4. Shoe outsole shape display program and creating data $\textbullet$ Contents 5. Conclusions