• Title/Summary/Keyword: network-based robot

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Position Estimation of Mobile Robots using Multiple Active Sensors with Network

  • Jin, Tae-Seok
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.4
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    • pp.280-285
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    • 2011
  • Recently, with the development of service robots and the concept of ubiquitous, the position estimation of mobile objects has received great interest. Some of the localization schemes are introduced, which provide the relative location of the moving objects subjected to accumulated errors. To implement a real time localization system, a new absolute position estimation method for a mobile robot in indoor environment is proposed. Design and implementation of the localization system comes from the usage of active beacon systems (based upon RFID technology). The active beacon system is composed of an RFID receiver and an ultra-sonic transmitter. The RFID receiver gets the synchronization signal from the mobile robot and the ultra-sonic transmitter sends out the traveling signal to be used for measuring the distance. Position of a mobile robot in a three dimensional space can be calculated basically from the distance information from three beacons and the absolute position information of the beacons themselves. In some case, the mobile robot can acquire the ultrasonic signals from only one or two beacons, due to the obstacles located along the moving path. In this paper, a position estimation scheme using fewer than three sensors is developed. Also, the extended Kalman filter algorithm is applied for the improvement of position estimation accuracy of the mobile robot.

A Testing Method for URC Robot Software (URC 로봇 소프트웨어 시험 평가 방법 및 사례 연구)

  • Hwang, Sun-Myung;Chung, Yun-Koo
    • The KIPS Transactions:PartD
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    • v.14D no.6
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    • pp.657-664
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    • 2007
  • URC robot offers necessary service anytime and anywhere by using a network to the robot, expanding the applicable service, keeping all the functions in itself, it undertakes functions for the causing problems through the network. URC software components are composed of HRI(Human Robot Interaction), robot action technology and others. We analyze the quality models based on ISO/IEC 9126, define URC components evaluation specification consists of 4 parts such as generic rule, instance rule, evaluation value and test method. And we define the quality process and test case design for URC, and show a testing and evaluation process for URC components.

Direct Adaptive Control System for Path Tracking of Mobile Robot Based on Wavelet Fuzzy Neural Network (이동 로봇의 경로 추종을 위한 웨이블릿 퍼지 신경 회로망 기반 직접 적응 제어 시스템)

  • Oh, Joon-Seop;Park, Jin-Bae;Choi, Yoon-Ho
    • Proceedings of the KIEE Conference
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    • 2004.07d
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    • pp.2432-2434
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    • 2004
  • In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.

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Development of Master-slave System for Robot-assisted Remote Ultrasound Diagnosis (로봇 지원 원격 초음파 영상진단을 위한 마스터-슬레이브 시스템의 개발)

  • Seo, Joonho;Cho, Jang Ho;Kwon, Ohwon
    • The Journal of Korea Robotics Society
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    • v.12 no.4
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    • pp.395-401
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    • 2017
  • In this paper, we introduce a robot-assisted medical diagnostic system that enables remote ultrasound (US) imaging to be applied to the conventional telemedicine, which has been possible only with interviewing or a visual exam. In particular, a master-slave robot system is developed that ultrasonic diagnosis specialist can control the position and orientation of US probe in the remote place. The slave robot is designed to be compact, lightweight, and hand-held so that it can easily transfer to the remote healthcare center. Moreover, 6-degree-of-freedom (DOF) probe motion is possible by the robot design based on Stewart platform. The master device is also based on a similar structure of the slave robot. To connect master and slave system in the wide area network (WAN) environment, a hardware CODEC was developed. In this paper, we introduce the detail of each component and the results of the recent experiments conducted in the remote sites by the developed robotic ultrasound imaging system.

USN based sonar localization system for a fish robot (물고기 로봇을 위한 USN 기반 초음파 측위 시스템)

  • Shin, Dae-Jung;Na, Seung-You;Kim, Jin-Young;Park, Aa-Ron
    • Journal of Sensor Science and Technology
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    • v.17 no.1
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    • pp.53-60
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    • 2008
  • Localization is the most important functions in mobile robots. There are so many approaches to realize this essential function in wheel based mobile robots, but it is not easy to find similar examples in small underwater robots. It is presented the sonar localization system using ubiquitous sensor network for a fish robot in this paper. A fish robot uses GPS and sonar system to find exact localization. Although GPS is essential tool to obtain positional information, this device doesn't provide reasonable resolution in localization. To obtain more precise localization information, we use several Ubiquitous Sensor Networks (USN) motes with sonar system. Experimental results show that a fish robot obtains more detailed positional information.

Autonomous Mobile Robot System based on a Fuzzy Artificial Immune System (퍼지 인공 면역망 시스템을 이용한 자율이동로봇 시스템)

  • Lee, Dong-Je;Choi, Young-Kui
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.257-260
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    • 2007
  • In this paper addresses the low-level behavior of fuzzy control and the high-level behavior selector for Autonomous Mobile Robots (AMRs) based on a Fuzzy Artificial Immune Network. The sensing information that comes from ultrasonic sensors is the antigen it, and stimulates antibodies. There are many possible combinations of actions between action-patterns and external situations. The question is how to handle the situations to decide the proper action. We propose a fuzzy artificial immune network to solve the above problem. and the computer simulation for an AMR action selector shows the usefulness of the proposed action selector.

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Robust Control of Industrial Robot Based on Back Propagation Algorithm (Back Propagation 알고리즘을 이용한 산업용 로봇의 견실 제어)

  • 윤주식;이희섭;윤대식;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2004.04a
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    • pp.253-257
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    • 2004
  • Neural networks are works are used in the framework of sensor based tracking control of robot manipulators. They learn by practice movements the relationship between PSD(an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple back propagation networks one of which is selected according to which division(corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

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Autonomous Mobile Robot Navigation using Artificial Immune Networks and Fuzzy Systems (인공 면역망과 퍼지 시스템을 이용한 자율이동로봇 주행)

  • Kim, Yang-Hyeon;Lee, Dong-Je;Lee, Min-Jung;Choe, Yeong-Gyu
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.51 no.9
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    • pp.402-412
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    • 2002
  • The navigation algorithms enable autonomous mobile robots to reach given target points without collision against obstacles. To achieve safe navigations in unknown environments, this paper presents an effective navigation algorithm for the autonomous mobile robots with ultrasonic sensors. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The fuzzy-based decision maker combines the steering angles from the target-reaching behavior and the obstacle-avoidance behavior in order to steer the autonomous mobile robot appropriately. Simulational and experimental results show that the proposed navigation algorithm is very effective in unknown environments.

Biologically inspired modular neural control for a leg-wheel hybrid robot

  • Manoonpong, Poramate;Worgotter, Florentin;Laksanacharoen, Pudit
    • Advances in robotics research
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    • v.1 no.1
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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.

Path Tracking Control Using a Wavelet Neural Network for Mobile Robot with Extended Kalman Filter

  • Oh, Joon-Seop;Park, Jin-Bae;Choi, Yoon-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2498-2501
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    • 2003
  • In this paper, we present a wavelet neural network (WNN) approach to the solution of the path tracking problem for mobile robots that possess complexity, nonlinearity and noise. First, we discuss a WNN based control system where the control signals are directly obtained by minimizing the difference between the reference track and the pose of a mobile robot. This compact network structure is helpful to determine the number of hidden nodes and the initial value of weights. Then, the data with various noises provided by odometric and external sensors are here fused together by means of an Extended Kalman Filter (EKF) approach for the pose estimation problem of mobile robots. This control process is a dynamic on-line process that uses the wavelet neural network trained via the gradient-descent method with estimates from EKF. Finally, we verify the effectiveness and feasibility of the proposed control system through simulations.

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