• Title/Summary/Keyword: the multiple cooperative robot system

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TWR based Cooperative Localization of Multiple Mobile Robots for Search and Rescue Application (재난 구조용 다중 로봇을 위한 GNSS 음영지역에서의 TWR 기반 협업 측위 기술)

  • Lee, Chang-Eun;Sung, Tae-Kyung
    • The Journal of Korea Robotics Society
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    • v.11 no.3
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    • pp.127-132
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    • 2016
  • For a practical mobile robot team such as carrying out a search and rescue mission in a disaster area, the localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a global positioning system (GPS) is unavailable. The proposed architecture supports localizing robots seamlessly by finding their relative locations while moving from a global outdoor environment to a local indoor position. The proposed schemes use a cooperative positioning system (CPS) based on the two-way ranging (TWR) technique. In the proposed TWR-based CPS, each non-localized mobile robot act as tag, and finds its position using bilateral range measurements of all localized mobile robots. The localized mobile robots act as anchors, and support the localization of mobile robots in the GPS-shadow region such as an indoor environment. As a tag localizes its position with anchors, the position error of the anchor propagates to the tag, and the position error of the tag accumulates the position errors of the anchor. To minimize the effect of error propagation, this paper suggests the new scheme of full-mesh based CPS for improving the position accuracy. The proposed schemes assuring localization were validated through experiment results.

Seamless Routing and Cooperative Localization of Multiple Mobile Robots for Search and Rescue Application

  • Lee, Chang-Eun;Im, Hyun-Ja;Lim, Jeong-Min;Cho, Young-Jo;Sung, Tae-Kyung
    • ETRI Journal
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    • v.37 no.2
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    • pp.262-272
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    • 2015
  • In particular, for a practical mobile robot team to perform such a task as that of carrying out a search and rescue mission in a disaster area, the network connectivity and localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a Global Positioning System is unavailable. This paper proposes the new collective intelligence network management architecture of multiple mobile robots supporting seamless network connectivity and cooperative localization. The proposed architecture includes a resource manager that makes the robots move around and not disconnect from the network link by considering the strength of the network signal and link quality. The location manager in the architecture supports localizing robots seamlessly by finding the relative locations of the robots as they move from a global outdoor environment to a local indoor position. The proposed schemes assuring network connectivity and localization were validated through numerical simulations and applied to a search and rescue robot team.

Analysis of dynamic manipulability for multiple cooperating robot system based on matrix decomposition (행렬 Decomposition 방법에 기초한 다중협동 로봇의 동적 조작도 해석)

  • 이지홍;조복기
    • Proceedings of the IEEK Conference
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    • 2003.07c
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    • pp.2705-2708
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    • 2003
  • In this paper, we propose a method that applies matrix decomposition technique to the connection of actuator capabilities of each robot to object acceleration limits for multiple cooperative robot systems. The robot systems under consideration are composed of several robot manipulators and each robot contacts a single object to carry the object while satisfying the constraints described in kinematics as well as dynamics. By manipulating kinematic and dynamic equations of both robots and objects, we at first derive a matrix relating joint torques with object acceleration, manipulate the null space of the matrix, and then we decompose the matrix into three parts representing indeterminancy, connectivity, and redundancy. With the decomposed matrix we derive the boundaries of object accelerations from given joint actuators. To show the validity of the proposed method some examples are given in which the results can be expected by intuitive observation.

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Study of Dynamic Analysis and Optimization for Control of Two Robots Simultaneously Grasping a Rigid Body Object (강체를 함께 쥔 두 대 로봇의 제어를 위한 동력학적 해석과 최적화 방안 연구)

  • 고진환;송문상;유범상;박상민
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.10a
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    • pp.507-512
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    • 1997
  • This paper presents a method of finding optitnal joint torques of two robots when they hold an object simultaneously. Although the importance of the multiple cooperating robot system increases for more flcviblc ni;mufacturing automation, dynamic solutions to multi-robot system forming closcd kinematic chain is not easy to find. Newton-Eulcr approach is used for the dynamic formulation of two robots fonn~ng closcd kincmatic chains gmsping a rigid body object. The nrcthodology to optimize the joint torques to satisfy given criterta and obtain bettcr control of the system is discussed. The scheme is illustrated by an example.

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VIRTUAL PASSIVITY-BASED DECENTRALIZED CONTROL OF MULTIPLE 3-WHEELED MOBILE ROBOTIC SYSTEMS VIA SYSTEM AUGMENTATION

  • SUH J. H.;LEE K. S.
    • International Journal of Automotive Technology
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    • v.6 no.5
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    • pp.545-554
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    • 2005
  • Passive velocity field control (PVFC) was previously developed for fully mechanical systems, in which the motion task was specified by behaviors in terms of a velocity field and the closed-loop was passive with respect to the supply rate given by the environment input. However, the PVFC was only applied to a single manipulator. The proposed control law was derived geometrically and the geometric and robustness properties of the closed-loop system were also analyzed. In this paper, we propose a virtual passivity-based algorithm to apply decentralized control to multiple 3­wheeled mobile robotic systems whose subsystems are under nonholonomic constraints and convey a common rigid object in a horizontal plain. Moreover, it is shown that multiple robot systems ensure stability and the velocities of augmented systems converge to a scaled multiple of each desired velocity field for cooperative mobile robot systems. Finally, the application of proposed virtual passivity-based decentralized algorithm via system augmentation is applied to trace a circle and the simulation results is presented in order to show effectiveness for the decentralized control algorithm proposed in this research.

Obstacle Avoidance Method for Multi-Agent Robots Using IR Sensor and Image Information (IR 센서와 영상정보를 이용한 다 개체 로봇의 장애물 회피 방법)

  • Jeon, Byung-Seung;Lee, Do-Young;Choi, In-Hwan;Mo, Young-Hak;Park, Jung-Min;Lim, Myo-Taeg
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.12
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    • pp.1122-1131
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    • 2012
  • This paper presents obstacle avoidance method for scout robot or industrial robot in unknown environment by using IR sensor and vision system. In the proposed method, robots share the information where the obstacles are located in real-time, thus the robots can choose the best path for obstacle avoidance. Using IR sensor and vision system, multiple robots efficiently evade the obstacles by the proposed cooperation method. No landmark is used at wall or floor in experiment environment. The obstacles don't have specific color or shape. To get the information of the obstacle, vision system extracts the obstacle coordinate by using an image labeling method. The information obtained by IR sensor is about the obstacle range and the locomotion direction to decide the optimal path for avoiding obstacle. The experiment was conducted in $7m{\times}7m$ indoor environment with two-wheeled mobile robots. It is shown that multiple robots efficiently move along the optimal path in cooperation with each other in the space where obstacles are located.

A Study on Swarm Robot-Based Invader-Enclosing Technique on Multiple Distributed Object Environments

  • Ko, Kwang-Eun;Park, Seung-Min;Park, Jun-Heong;Sim, Kwee-Bo
    • Journal of Electrical Engineering and Technology
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    • v.6 no.6
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    • pp.806-816
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    • 2011
  • Interest about social security has recently increased in favor of safety for infrastructure. In addition, advances in computer vision and pattern recognition research are leading to video-based surveillance systems with improved scene analysis capabilities. However, such video surveillance systems, which are controlled by human operators, cannot actively cope with dynamic and anomalous events, such as having an invader in the corporate, commercial, or public sectors. For this reason, intelligent surveillance systems are increasingly needed to provide active social security services. In this study, we propose a core technique for intelligent surveillance system that is based on swarm robot technology. We present techniques for invader enclosing using swarm robots based on multiple distributed object environment. The proposed methods are composed of three main stages: location estimation of the object, specified object tracking, and decision of the cooperative behavior of the swarm robots. By using particle filter, object tracking and location estimation procedures are performed and a specified enclosing point for the swarm robots is located on the interactive positions in their coordinate system. Furthermore, the cooperative behaviors of the swarm robots are determined via the result of path navigation based on the combination of potential field and wall-following methods. The results of each stage are combined into the swarm robot-based invader-enclosing technique on multiple distributed object environments. Finally, several simulation results are provided to further discuss and verify the accuracy and effectiveness of the proposed techniques.

Learning soccer robot using genetic programming

  • Wang, Xiaoshu;Sugisaka, Masanori
    • 제어로봇시스템학회:학술대회논문집
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    • 1999.10a
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    • pp.292-297
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    • 1999
  • Evolving in artificial agent is an extremely difficult problem, but on the other hand, a challenging task. At present the studies mainly centered on single agent learning problem. In our case, we use simulated soccer to investigate multi-agent cooperative learning. Consider the fundamental differences in learning mechanism, existing reinforcement learning algorithms can be roughly classified into two types-that based on evaluation functions and that of searching policy space directly. Genetic Programming developed from Genetic Algorithms is one of the most well known approaches belonging to the latter. In this paper, we give detailed algorithm description as well as data construction that are necessary for learning single agent strategies at first. In following step moreover, we will extend developed methods into multiple robot domains. game. We investigate and contrast two different methods-simple team learning and sub-group loaming and conclude the paper with some experimental results.

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Detection of Faces Located at a Long Range with Low-resolution Input Images for Mobile Robots (모바일 로봇을 위한 저해상도 영상에서의 원거리 얼굴 검출)

  • Kim, Do-Hyung;Yun, Woo-Han;Cho, Young-Jo;Lee, Jae-Jeon
    • The Journal of Korea Robotics Society
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    • v.4 no.4
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    • pp.257-264
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    • 2009
  • This paper proposes a novel face detection method that finds tiny faces located at a long range even with low-resolution input images captured by a mobile robot. The proposed approach can locate extremely small-sized face regions of $12{\times}12$ pixels. We solve a tiny face detection problem by organizing a system that consists of multiple detectors including a mean-shift color tracker, short- and long-rage face detectors, and an omega shape detector. The proposed method adopts the long-range face detector that is well trained enough to detect tiny faces at a long range, and limiting its operation to only within a search region that is automatically determined by the mean-shift color tracker and the omega shape detector. By focusing on limiting the face search region as much as possible, the proposed method can accurately detect tiny faces at a long distance even with a low-resolution image, and decrease false positives sharply. According to the experimental results on realistic databases, the performance of the proposed approach is at a sufficiently practical level for various robot applications such as face recognition of non-cooperative users, human-following, and gesture recognition for long-range interaction.

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A Study on the Parallel Escape Maze through Cooperative Activities of Humanoid Robots (인간형 로봇들의 협력 작업을 통한 미로 동시 탈출에 관한 연구)

  • Jun, Bong-Gi
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.6
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    • pp.1441-1446
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    • 2014
  • For the escape from a maze, the cooperative method by robot swarm was proposed in this paper. The robots can freely move by collecting essential data and making a decision in the use of sensors; however, a central control system is required to organize all robots for the escape from the maze. The robots explore new mazes and then send the information to the system for analyzing and mapping the escaping route. Three issues were considered as follows for the effective escape by multiple robots from the mazes in this paper. In the first, the mazes began to divide and secondly, dead-ends should be blocked. Finally, after the first arrivals at the destination, a shortcut should be provided for rapid escaping from the maze. The parallel-escape algorithms were applied to the different size of mazes, so that robot swarm can effectively get away the mazes.