• Advances in robotics research
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• 제1권1호
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• pp.101-126
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• 2014

In this article we present modular neural control for a leg-wheel hybrid robot consisting of three legs with omnidirectional wheels. This neural control has four main modules having their functional origin in biological neural systems. A minimal recurrent control (MRC) module is for sensory signal processing and state memorization. Its outputs drive two front wheels while the rear wheel is controlled through a velocity regulating network (VRN) module. In parallel, a neural oscillator network module serves as a central pattern generator (CPG) controls leg movements for sidestepping. Stepping directions are achieved by a phase switching network (PSN) module. The combination of these modules generates various locomotion patterns and a reactive obstacle avoidance behavior. The behavior is driven by sensor inputs, to which additional neural preprocessing networks are applied. The complete neural circuitry is developed and tested using a physics simulation environment. This study verifies that the neural modules can serve a general purpose regardless of the robot's specific embodiment. We also believe that our neural modules can be important components for locomotion generation in other complex robotic systems or they can serve as useful modules for other module-based neural control applications.

• 한국안전학회지
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• 제31권5호
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• pp.28-34
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• 2016

When a electric power cable is installed in the air for newly or exchanged working, it is necessary at all time to hold a constant tension for an overhead power cable. And also a pendanted power cable is an extreme job to have work in a high sky. For this reason, the objective of this paper developments working robot for preventing disaster that tension of cable installed automatically power cable to hold a constant. So the working robot works at all the time two tasks for mobil and tension it come into a inference between two tasks, control is difficult. Control methode needs to suppress inference of two tasks. In this paper, for installation of overhead power cable, the scheme and control methode of working robot is presented. the robot work at a same time tow tasks that have hold a constant tension of the power cable and move a constant place while unfasten a winding cable at a drum on a chassis. Working robot consist of three parts with mobile system, tension system and control part. As it is applied the feedback/feedforward control, methode of hybrid control is established to suppress that interference come into between two tasks. The simulation programs is made out using models of mobil and tension system, and a proposed controllers. In accordance with simulation, the model of each systems is discussed to make out proper. And also parameters of controllers is selected a suitable value and the driving performance of robot is evaluated.

• Journal of Advanced Marine Engineering and Technology
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• 제38권10호
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• pp.1287-1296
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• 2014

This paper is about control of Automated Guided Vehicle for path following using fuzzy logic controller. The Automated Guided Vehicle is a tricycle wheeled mobile robot with three wheels, two fixed passive wheels and one steering driving wheel. First, kinematic and dynamic modeling for Automated Guided Vehicle is presented. Second, a controller that integrates two control loops, kinematic control loop and dynamic control loop, is designed for Automated Guided Vehicle to follow an unknown path. The kinematic control loop based on Fuzzy logic framework and the dynamic control loop based on two PID controllers are proposed. Simulation and experimental results are presented to show the effectiveness of the proposed controllers.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.882-887
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• 2005

The paper describes Quasi-simultaneous recognition of plural targets and motion control of robot based on the recognition. The method searches for targets by model-based matching method using the hybrid GA, and the motion of the robot is generated based on the targets' positions on the image. The method is applied to a soccer robot, and targets are a ball, a goal, and an enemy in the experiment. The Experimental results show robustness and reliability of the proposed method.

• Nuclear Engineering and Technology
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• 제55권5호
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• pp.1838-1854
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• 2023

This paper presents a hybrid algorithm to solve the multi-objective path planning (MOPP) problem for mobile robots in a static nuclear accident environment. The proposed algorithm mimics a real nuclear accident site by modeling the environment with a two-layer cost grid map based on geometric modeling and Monte Carlo calculations. The proposed algorithm consists of two steps. The first step optimizes a path by the hybridization of improved ant colony optimization algorithm-modified A^* (IACO-A^*) that minimizes path length, cumulative radiation dose and energy consumption. The second module is the high radiation dose rate avoidance strategy integrated with the IACO-A^* algorithm, which will work when the mobile robots sense the lethal radiation dose rate, avoiding radioactive sources with high dose levels. Simulations have been performed under environments of different complexity to evaluate the efficiency of the proposed algorithm, and the results show that IACO-A^* has better path quality than ACO and IACO. In addition, a study comparing the proposed IACO-A^* algorithm and recent path planning (PP) methods in three scenarios has been performed. The simulation results show that the proposed IACO-A^* IACO-A^* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 심포지엄 논문집 정보 및 제어부문
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• pp.77-78
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• 2008

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

• 한국태양에너지학회 논문집
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• 제34권4호
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• pp.123-129
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• 2014

Photovoltaic and fuel cell systems can be used as power source in mobile robots. At this time the photovoltaic system generally generate power in daytime. The starting time of fuel cell is slower than the lithium battery. To compensate for these disadvantages, a battery charge-discharge system is used. Especially the bi-directional converter is used mainly in the charge-discharge method. The controller in a buck converter controls the input voltage of the converter to meet the maximum power point tracking(MPPT) performance. First of all, the simulations of hybrid system for battery charge-discharge system in each step simulated using solar and fuel cell modeling as input source in PSIM. Experiment of the buck and bi-directional converter system is conducted through using photovoltaic/fuel cel simulator(pCube) instead of solar and fuel cell. This hybrid system for battery charge discharge using photovoltaic/fuel cell generates emergency power for the communication system in mobile robot.

• 한국항행학회논문지
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• 제15권6호
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• pp.1143-1151
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• 2011

본 논문은 각 기관별로 운영되고 있는 게시판 정보를 하나로 통합하여 클라우드 기반의 스마트폰 환경에서 사용자가 원하는 정보를 제공해주는 하이브리드 웹 기반 통합 시스템을 구현하였다. 본 시스템은 대학의 각 기관에서 운영되고 있는 웹 서버의 게시물 정보를 적절한 시간 간격으로 수집하여 저장 및 관리하는 SaaS 서비스의 웹로봇과 스마트 폰의 UI를 통한 사용자에게 정보를 제공하는 게시물관리 PaaS 서버로 구성된다. 또한, 스마트폰 사용자의 GPS 정보를 활용하여 새로운 게시물의 정보를 알려주는 알리미 어플을 구현하였다.

• 한국정밀공학회지
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• 제26권6호
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• pp.59-67
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• 2009

This paper addresses the control method for skating motion with a nonholonomic constraint. In order to generate a human-like skating motion, the behaviors of motion are distinctively analyzed into transient state and steady state. A close investigation of the behaviors evolved the characteristic of successive motions with transient state and steady state. Simulation results were intuitively comprehensible, and the effectiveness of control method was demonstrated for skating motion.

• 전기학회논문지
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• 제58권8호
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• pp.1605-1614
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• 2009

The technique of simultaneous localization and mapping is the most important research topic in mobile robotics. In the process of building a map in its available memory, the robot memorizes environmental information on the plane of grid or topology. Several approaches about this technique have been presented so far, but most of them use mapping technique as either grid-based map or topology-based map. In this paper we propose a frame of solving the SLAM problem of linking map covering, map building, localizing, path finding and obstacle avoiding in an automatic way. Some algorithms integrating grid and topology map are considered and this make the SLAM performance faster and more stable. The proposed scheme uses an occupancy grid map in representing the environment and then formulate topological information in path finding by A${\ast}$ algorithm. The mapping process is shown and the shortest path is decided on grid based map. Then topological information such as direction, distance is calculated on simulator program then transmitted to robot hardware devices. The localization process and the dynamic obstacle avoidance can be accomplished by topological information on grid map. While mapping and moving, pose of the robot is adjusted for correct localization by implementing additional pixel based image layer and tracking some features. A laser range finer and electronic compass systems are implemented on the mobile robot and DC geared motor wheels are individually controlled by the adaptive PD control method. Simulations and experimental results show its performance and efficiency of the proposed scheme are increased.