• Journal of Information Processing Systems
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• 제11권3호
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• pp.370-388
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• 2015

The localization of multi-agents, such as people, animals, or robots, is a requirement to accomplish several tasks. Especially in the case of multi-robotic applications, localization is the process for determining the positions of robots and targets in an unknown environment. Many sensors like GPS, lasers, and cameras are utilized in the localization process. However, these sensors produce a large amount of computational resources to process complex algorithms, because the process requires environmental mapping. Currently, combination multi-robots or swarm robots and sensor networks, as mobile sensor nodes have been widely available in indoor and outdoor environments. They allow for a type of efficient global localization that demands a relatively low amount of computational resources and for the independence of specific environmental features. However, the inherent instability in the wireless signal does not allow for it to be directly used for very accurate position estimations and making difficulty associated with conducting the localization processes of swarm robotics system. Furthermore, these swarm systems are usually highly decentralized, which makes it hard to synthesize and access global maps, it can be decrease its flexibility. In this paper, a simple pyramid RAM-based Neural Network architecture is proposed to improve the localization process of mobile sensor nodes in indoor environments. Our approach uses the capabilities of learning and generalization to reduce the effect of incorrect information and increases the accuracy of the agent's position. The results show that by using simple pyramid RAM-base Neural Network approach, produces low computational resources, a fast response for processing every changing in environmental situation and mobile sensor nodes have the ability to finish several tasks especially in localization processes in real time.

• 한국정밀공학회지
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• 제30권1호
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• pp.11-17
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• 2013

'Multi-scale mass-deployable cooperative robots' is a next generation robotics paradigm where a large number of robots that vary in size cooperate in a hierarchical fashion to collect information in various environments. While this paradigm can exhibit the effective solution for exploration of the wide area consisting of various types of terrain, its technical maturity is still in its infant state and many technical hurdles should be resolved to realize this paradigm. In this paper, we propose to develop new design and manufacturing methodologies for the multi-scale mass-deployable cooperative robots. In doing so, we present various fundamental technologies in four different research fields. (1) Adaptable design methods consist of compliant mechanisms and hierarchical structures which provide robots with a unified way to overcome various and irregular terrains. (2) Soft composite materials realize the compliancy in these structures. (3) Multi-scale integrative manufacturing techniques are convergence of traditional methods for producing various sized robots assembled by such materials. Finally, (4) the control and communication techniques for the massive swarm robot systems enable multiple functionally simple robots to accomplish the complex job by effective job distribution.

• 디지털융복합연구
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• 제12권6호
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• pp.349-354
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• 2014

이 논문에서는 여러 대의 로봇들이 협력하여 미로를 탈출하는 방법을 제안한다. 논문에서 사용된 교육용 로봇들은 ZigBee로 서로 통신할 수 있으나, 로봇들의 연산기능이 낮아 서로 협력하여 문제를 해결할 수 없다. 로봇의 모션제어로 통로를 직립 보행하도록 하였으며, 절대거리 센서를 이용하여 교차로와 막다른 골목을 인식하면 중앙제어 시스템에 전송하여 명령을 받는다. 여러 로봇들이 동시에 미로에 들어가서 효과적으로 미로를 탐색하도록 하는 미로 탐색 알고리즘을 수정하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.337-339
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• 2007

This paper proposes a new paradigm for cooperation of multi-robot system for home service. For localization of each robot. the master robot collects information of location of each robot based on communication of RFID tag on the floor and RFID reader attached on the bottom of the robot. The Master robot communicates with slave robots via wireless LAN to check the motion of robots and command to them based on the information from slave robots. The operator may send command to slave robots based on the HRI(Human-Robot Interaction) screened on masted robot using information from slave robots. The cooperation of multiple robots will enhance the performance comparing with single robot.

• 로봇학회논문지
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• 제4권1호
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• pp.10-16
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• 2009

This paper is concerned with Korean students' attitudes towards robots, presenting two survey studies. The first study was concerned with a group of college students, taking the perspective of international comparison. Data were collected by administering an online survey, where 106 volunteer students had participated. In the survey, the Negative Attitude towards Robot Scale(NARS) was adopted to compare the Korean students' scores with those of multi-national groups (U.S.A, Germany, Netherland, Japan, Mexico, and China) who responded to the same scale in Bartneck et al.'s research. The analysis of the data reveals that Korean students tend to be more concerned about social impacts that robots might bring to future society and are very conscious about the uncertain influences of robots on human life. The second study investigated factors that may affect K-12 students' attitudes towards robots, with survey data garnered from 298 elementary, middle, and high school students. The data were analyzed by the method of multiple regression analysis to test the hypothesis that a student's gender, age, the extent of interest in robots, and the extent of experiences with robots may influence his or her attitude towards robots. The hypothesis was partially supported in that variables of a student's gender, age, and the extent of interest in robots were statistically significant with regard to the attitude variable. Given the results, this paper suggests three points of discussions to better understand Korean students' attitudes towards robots: social and cultural context, individual differences, and theory of mind.

• Journal of Computational Design and Engineering
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• 제2권3호
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• pp.157-164
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• 2015

This paper discusses an optimization-based approach for the design of a product platform for industrial three-axis linear-type robots, which are widely used for handling objects in manufacturing lines. Since the operational specifications of these robots, such as operation speed, working distance and orientation, weight and shape of loads, etc., will vary for different applications, robotic system vendors must provide various types of robots efficiently and effectively to meet a range of market needs. A promising step toward this goal is the concept of a product platform, in which several key elements are commonly used across a series of products, which can then be customized for individual requirements. However the design of a product platform is more complicated than that of each product, due to the need to optimize the design across many products. This paper proposes an optimization-based fundamental framework toward the design of a product platform for industrial three-axis linear-type robots; this framework allows the solution of a complicated design problem and builds an optimal design method of fundamental features of robot frames that are commonly used for a wide range of robots. In this formulation, some key performance metrics of the robot are estimated by a reducedorder model which is configured with beam theory. A multi-objective optimization problem is formulated to represent the trade-offs among key design parameters using a weighted-sum form for a single product. This formulation is integrated into a mini-max type optimization problem across a series of robots as an optimal design formulation for the product platform. Some case studies of optimal platform design for industrial three-axis linear-type robots are presented to demonstrate the applications of a genetic algorithm to such mathematical models.

• 한국통신학회논문지
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• 제33권11B호
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• pp.1030-1037
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• 2008

본 논문에서는 다중 로봇 (multi-robot)을 활용한 응용분야 중, 미지의 영역에 대한 탐색 (exploration) 능력을 향상시켜서, 주어진 미로 (maze)에서 다중 로봇이 통신을 통해서 협력적으로 출구를 찾아가는 효율적인 방안을 제안하였다. 즉, 미로 형태의 임의의 환경을 생성한 후, 로봇을 무작위로 배치시켜 상호간에 통신을 통하여 출구로 신속히 모두 빠져나오는 문제를 다루고 있다. 미로탐색을 위해 다중 로봇의 지역 탐색에서 사용되었던, 프론티어 셀, 셀 유틸리티등 기존 연구를 활용하였다. 또한 로봇간의 다중홉 무선 통신 (multihop wireless communications)을 위해서 이동성 (mobility)에 강한 일종의 홉기반 (hop-by-hop) 라우팅인, 랜덤 베스킷 볼 라우팅을 채용하였다. 또한, 출구를 찾은 로봇이 일정한 확률에 의거하여 출구 앞에서 정지하거나 혹은, 빠져나가는 의사 결정을 하여, 이 확률적인 결정이 다른 로봇의 행동에 어떻게 영향을 주는지를 실험적으로 조사하였다. 즉, 출구를 찾은 로봇이 현재 위치에서 멈추어서, 통신 중계 지점 (relay)으로 어떻게 활동되어야 최적인지에 대한 문제를 모의 실험을 통해 파악해보았다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.165-171
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• 2004

Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

• 제어로봇시스템학회논문지
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• 제17권10호
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

• 한국군사과학기술학회지
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• 제27권5호
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• pp.619-627
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• 2024

As AI technology advances, interest in performing multi-robot autonomous missions for manned-unmanned teaming (MUM-T) is increasing. In order to develop autonomous mission performance technology for multiple robots, simulation technology that reflects the characteristics of real robots and can flexibly apply various missions is needed. Additionally, in order to solve complex non-linear tasks, an API must be provided to apply multi-robot reinforcement learning technology, which is currently under active research. In this study, we propose the campaign model to flexibly simulate the missions of multiple robots. We then discuss the results of developing a simulation environment that can be edited and run and provides a reinforcement learning API including acceleration performance. The proposed simulated control module and simulated environment were verified using an enemy infiltration scenario, and parallel processing performance for efficient reinforcement learning was confirmed through experiments.