• 제목/요약/키워드: 소프트 로봇

검색결과 184건 처리시간 0.032초

Experimental Performance Validation of an Unmanned Surface Vessel System for Wide-Area Sensing and Monitoring of Hazardous and Noxious Substances (HNS 광역 탐지 및 모니터링을 위한 부유식 무인이동체 시스템의 실험적 성능 검증)

  • Jinwook Park;Jinsik Kim;Jinwhan Kim;Yongmyung Kim;Moonjin Lee
    • Journal of the Korean Society of Marine Environment & Safety
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    • 제28권spc호
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    • pp.11-17
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    • 2022
  • In this study, we address the development of a floating platform system based on a unmanned surface vessel for wide-area sensing and monitoring of hazardous and noxious substances (HNSs). For long endurance, a movable floating platform with no mooring lines was used and modified for HNS sensing and monitoring. The floating platform was equipped with various sensors such as optical and thermal imaging cameras, marine radar, and sensors for detecting HNSs in water and air. Additionally, for experiment validation in real outdoor environments, a portable gas-exposure system (PGS) was built and installed on the monitoring system. The software for carrying out the mission was integrated with the Robot Operating System (ROS) framework. The practical feasibility of the developed system was verified through experimental tests conducted in inland water and real-sea environments.

Characteristics of Integrated Aging-friendly Technologies into Future Smart Housing (미래주택에 적용될 고령친화기술의 특성연구)

  • Cui, Jing yu;Lee, Yeun sook;Hwang, Ji hye
    • Design Convergence Study
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    • 제15권2호
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    • pp.1-15
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    • 2016
  • The purpose of this study is to identify the characteristics of aging-friendly technology that can be integrated into future smart homes in an aging society. The literature survey and content analysis method were used to collect and analyze data. Papers of the international journal ICOST (International Conference on Smart Homes and Health Telematics) that professionally deal with converged technologies were analysis units. Sixty-five papers among 215 papers published from 2007 through 2014 were selected on the basis of end-users orientation. Totally, out of 65 papers 76 technology items were extracted. Characteristics of those technologies were analyzed focusing on purpose and application methods. As results, in terms of purpose, the technologies were oriented to provide both of psychological and physiological support to the users, focusing on the safety, convenience, health and entertainment to extend independent life of the elderly. Among the application method such as building structure, furniture, product, wearable device and free movable robot, product were dominant. Through those results, the aging-friendly technology is expected to alleviate a wide range of issues in aging society.

A Design of Static Meta-Model for Reuse Framework of Embedded System (임베디드 시스템의 재사용 프레임워크를 위한 정적 메타모델 설계)

  • Cho, Eun-Sook;Kim, Chul-Jin;Lee, Sook-Hee
    • Journal of Korea Multimedia Society
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    • 제12권2호
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    • pp.231-243
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    • 2009
  • Currently interests of embedded software in various areas such as automotive field, ship field, robot field is increasing according to expand market of embedded systems. Various researches such as embedded operating systems, embedded software modeling technique, embedded software testing, and so on are going in progress. However systematic engineering approach in embedded system development is poor because embedded areas focus on hardware parts until now. Furthermore, framework-based de sign technique considering reusability is not reflected in embedded system development. Those development results in many of dead codes scattered in system, and results in poor reusability of system. This paper suggests a framework of embedded system for reusability and a static meta-model for reuse framework. Proposed meta-model expresses not only the structure of reuse framework, but also allows a designer to extend and design easily models of embedded system based on reuse framework according to various embedded system types.

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Automatic Object Recognition in 3D Measuring Data (3차원 측정점으로부터의 객체 자동인식)

  • Ahn, Sung-Joon
    • The KIPS Transactions:PartB
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    • 제16B권1호
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    • pp.47-54
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    • 2009
  • Automatic object recognition in 3D measuring data is of great interest in many application fields e.g. computer vision, reverse engineering and digital factory. In this paper we present a software tool for a fully automatic object detection and parameter estimation in unordered and noisy point clouds with a large number of data points. The software consists of three interactive modules each for model selection, point segmentation and model fitting, in which the orthogonal distance fitting (ODF) plays an important role. The ODF algorithms estimate model parameters by minimizing the square sum of the shortest distances between model feature and measurement points. The local quadric surface fitted through ODF to a randomly touched small initial patch of the point cloud provides the necessary initial information for the overall procedures of model selection, point segmentation and model fitting. The performance of the presented software tool will be demonstrated by applying to point clouds.

An Intelligent Moving Wireless Camera Surveillance System with Motion sensor and Remote Control (무선조종과 모션 센서를 이용한 지능형 이동 무선감시카메라 구현)

  • Lee, Young Woong;Kim, Jong-Nam
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 한국해양정보통신학회 2009년도 춘계학술대회
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    • pp.661-664
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    • 2009
  • Recently, intelligent surveillance camera systems are needed popularly. However, current researches are focussed on improvement of a single module rather than implementation of an integrated system. In this paper, we implemented a moving wireless surveillance camera system which is composed of face detection, and using motion sensor. In our implementation, we used a camera module from SHARP, a pair of wireless video transmission module from ECOM, body of moving robot used for A4WD1 Combo kit for RC, a pair of ZigBee RF wireless transmission module from ROBOBLOCK, and a motion sensor module (AMN14111) from PANASONIC. We used OpenCV library for face dection and MFC for implement software. We identified real-time operations of face detection, PTT control, and motion sensor detecton. Thus, the implemented system will be useful for the applications of remote control, human detection, and using motion sensor.

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A study on Energy Conversion through Torque Control of IPMSM in EV Powertrain (EV 파워트레인에서 IPMSM의 토크 제어를 통한 에너지 변환에 관한 연구)

  • Baek, Soo-Whang
    • The Journal of the Korea institute of electronic communication sciences
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    • 제16권5호
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    • pp.845-850
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    • 2021
  • In this study, the energy conversion characteristics and design of electric vehicle (EV: Electric Vehicle) powertrain were performed. An interior permanent magnet synchronous motor (IPMSM) was targeted as a power source for the EV powertrain, and control was performed. In order to drive the IPMSM, two regions are considered: a constant torque and a constant output (field-weakening) region. The design of the control system for IPMSM was constructed based on the d-q reference frame (vector control). To determine the static characteristics of motor torque appearing in two areas of IPMSM, a torque control system and a d axis current control system of IPMSM were implemented and proposed. Matlab-Simulink software was used for characteristic analysis. Finally, by applying IPMSM to the powertrain model under the actual EV vehicle level conditions, simulation results of the proposed control system were performed and characteristics were analyzed.

A Review on Deep Learning Platform for Artificial Intelligence (인공지능 딥러링 학습 플랫폼에 관한 선행연구 고찰)

  • Jin, Chan-Yong;Shin, Seong-Yoon;Nam, Soo-Tai
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 한국정보통신학회 2019년도 춘계학술대회
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    • pp.169-170
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    • 2019
  • Lately, as artificial intelligence becomes a source of global competitiveness, the government is strategically fostering artificial intelligence that is the base technology of future new industries such as autonomous vehicles, drones, and robots. Domestic artificial intelligence research and services have been launched mainly in Naver and Kakao, but their size and level are weak compared to overseas. Recently, deep learning has been conducted in recent years while recording innovative performance in various pattern recognition fields including speech recognition and image recognition. In addition, deep running has attracted great interest from industry since its inception, and global information technology companies such as Google, Microsoft, and Samsung have successfully applied deep learning technology to commercial products and are continuing research and development. Therefore, we will look at artificial intelligence which is attracting attention based on previous research.

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Case Study of Building a Malicious Domain Detection Model Considering Human Habitual Characteristics: Focusing on LSTM-based Deep Learning Model (인간의 습관적 특성을 고려한 악성 도메인 탐지 모델 구축 사례: LSTM 기반 Deep Learning 모델 중심)

  • Jung Ju Won
    • Convergence Security Journal
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    • 제23권5호
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    • pp.65-72
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    • 2023
  • This paper proposes a method for detecting malicious domains considering human habitual characteristics by building a Deep Learning model based on LSTM (Long Short-Term Memory). DGA (Domain Generation Algorithm) malicious domains exploit human habitual errors, resulting in severe security threats. The objective is to swiftly and accurately respond to changes in malicious domains and their evasion techniques through typosquatting to minimize security threats. The LSTM-based Deep Learning model automatically analyzes and categorizes generated domains as malicious or benign based on malware-specific features. As a result of evaluating the model's performance based on ROC curve and AUC accuracy, it demonstrated 99.21% superior detection accuracy. Not only can this model detect malicious domains in real-time, but it also holds potential applications across various cyber security domains. This paper proposes and explores a novel approach aimed at safeguarding users and fostering a secure cyber environment against cyber attacks.

Design Factor Analysis of End-Effector for Oriental Melon Harvesting Robot in Greenhouse Cultivation (시설재배 참외 수확 로봇용 엔드이펙터의 설계 요인 분석)

  • Ha, Yu Shin;Kim, Tae Wook
    • Journal of Bio-Environment Control
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    • 제22권3호
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    • pp.284-290
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    • 2013
  • This study analyzed the geometric, compressive, cutting and friction properties of oriental melons in order to design a gripper capable of soft handling and a cutter for cutting oriental melon vine among the end effector of oriental melon as a preliminary step for developing the end effector of the robot capable of harvesting oriental melons in protected cultivation. As a result, the average length, diameter at the midpoint, weight, volume and roundness of the oriental melons were 108 mm, 70 mm, 188 g, 333 mL and 3.8 mm. Nonlinear regression analysis was performed on the equation $W=L^a{\times}D_2^b$ with variation of the length (L) and diameter (D2) of the weight (W) of the oriental melons. As a result, it was shown that there was a correlation between a of 2.0279 and b of -0.9998 as a constant value. The average diameter of the oriental melon vine was 3.8 mm, and most vines were distributed within a radius of 5 mm from the center. The average yield value, compressive strength and hardness of the oriental melons were $36.5N/cm^2$, $185.7N/cm^2$ and $636.7N/cm^2$, respectively. The average cutting force and shear strength of the oriental melon vines were $2.87{\times}10^{-2}\;N$ and $5.60N/cm^2$, respectively. The maximum friction coefficient of the oriental melons was rubber of 0.609, followed by aluminium of 0.393, stainless steel of 0.177 and teflon of 0.079. It was considered possible to apply it to the size of the gripper and cutter, turning radius, dynamics of drive motor and selection of materials and their quality in light of the position error and safety factor according to the movement when designing end effector based on the analyzed data.

Appropriate Smart Factory : Demonstration of Applicability to Industrial Safety (적정 스마트공장: 산업안전 기술로의 적용 가능성 실증)

  • Kwon, Kui-Kam;Jeong, Woo-Kyun;Kim, Hyungjung;Quan, Ying-Jun;Kim, Younggyun;Lee, Hyunsu;Park, Suyoung;Park, Sae-Jin;Hong, SungJin;Yun, Won-Jae;Jung, Guyeop;Lee, Gyu Wha;Ahn, Sung-Hoon
    • Journal of Appropriate Technology
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    • 제7권2호
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    • pp.196-205
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    • 2021
  • As industrial safety increases, various industrial accident prevention technologies using smart factory technology are being studied. However, small and medium enterprises (SMEs), which account for the majority of industrial accidents, are having difficulties in preventing industrial accidents by applying these smart factory technologies due to practical problems. In this study, customized monitoring and warning systems for each type of industrial accident were developed and applied to the actual field. Through this, we demonstrated industrial accident prevention technology through appropriate smart factory technology used by SMEs. A customized monitoring system using vision, current, temperature, and gas sensors was established for the four major disaster types: worker body access, short circuit and overcurrent, fire and burns due to high temperature, and emission of hazardous gas. In addition, a notification method suitable for each work environment was applied so that the monitored risk factors could be recognized quickly, and real-time data transmission and display enabled workers and managers to understand the disaster risk effectively. Through the application and demonstration of these appropriate smart factory technologies, the spread of these industrial safety technologies is to be discussed.