• Title/Summary/Keyword: industrial robots

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Trend Analysis of Convergence Research based on Social Big Data (소셜 빅데이터 기반 융합연구 동향 분석)

  • Noh, Younghee;Kim, Taeyoun;Jeong, Dae-Keun;Lee, Kwang Hee
    • The Journal of the Korea Contents Association
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    • v.19 no.2
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    • pp.135-146
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    • 2019
  • This study was designed to analyze trends in the entire convergence research beyond academic research through social media big data analysis at a time when interdisciplinary convergence research is emphasized along with the fourth industrial revolution. For this purpose, about 150,000 cases of texts and titles were acquired for about 10 years from January 2009 to September 2018 in connection with the convergence research in social media, and word cloud and network analysis were conducted. As a results, the research fields that were actively conducted for each period were eco-tech in 2009 and 2010, smart technology in 2011 and 2012, information and communication in 2013 and 2014, robots in 2015 and 2016, and artificial intelligence in 2017 and 2018. Also, the research areas that have been consistently conducted for about 10 years are culture, design, chemistry, nanotechnology, biotechnology, robot, IT, and information and communication. Since this study identifies trends in convergence research over time, it can be helpful to researchers who are planning convergence research direction by understanding the trends of convergence research.

Development of Reinforcement Learning-based Obstacle Avoidance toward Autonomous Mobile Robots for an Industrial Environment (산업용 자율 주행 로봇에서의 격자 지도를 사용한 강화학습 기반 회피 경로 생성기 개발)

  • Yang, Jeong-Yean
    • The Journal of the Korea Contents Association
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    • v.19 no.3
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    • pp.72-79
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    • 2019
  • Autonomous locomotion has two essential functionalities: mapping builds and updates maps by uncertain position information and measured sensor inputs, and localization is to find the positional information with the inaccurate map and the sensor information. In addition, obstacle detection, avoidance, and path designs are necessarily required for autonomous locomotion by combining the probabilistic methods based on uncertain locations. The sensory inputs, which are measured by a metric-based scanner, have difficulties of distinguishing moving obstacles like humans from static objects like walls in given environments. This paper proposes the low resolution grid map combined with reinforcement learning, which is compared with the conventional recognition method for detecting static and moving objects to generate obstacle avoiding path. Finally, the proposed method is verified with experimental results.

Hacking attack and vulnerability analysis for unmanned reconnaissance Tankrobot (무인정찰 탱크로봇에 대한 해킹 공격 및 취약점 분석에 관한 연구)

  • Kim, Seung-woo;Park, Dea-woo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.9
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    • pp.1187-1192
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    • 2020
  • The dronebot combat system is a representative model of the future battlefield in the 4th industrial revolution. In dronebot, unmanned reconnaissance tankrobot can minimize human damage and reduce cost with higher combat power than humans. However, since the battlefield environment is very complex such as obstacles and enemy situations, it is also necessary for the pilot to control the tankrobot. Tankrobot are robots with new ICT technology, capable of hacking attacks, and if there is an abnormality in control, it can pose a threat to manipulation and control. A Bluetooth sniffing attack was performed on the communication section of the tankrobot and the controller to introduce a vulnerability to Bluetooth, and a countermeasure using MAC address exposure prevention and communication section encryption was proposed as a security measure. This paper first presented the vulnerability of tankrobot to be operated in future military operations, and will be the basic data that can be used for defense dronebot units.

Numerical and experimental investigation for monitoring and prediction of performance in the soft actuator

  • Azizkhani, Mohammadbagher;sangsefidi, Alireza;Kadkhodapour, Javad;Anaraki, Ali Pourkamali
    • Structural Engineering and Mechanics
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    • v.77 no.2
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    • pp.167-177
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    • 2021
  • Due to various benefits such as unlimited degrees of freedom, environment adaptability, and safety for humans, engineers have used soft materials with hyperelastic behavior in various industrial, medical, rescue, and other sectors. One of the applications of these materials in the fabrication of bending soft actuators (SA) is that they have eliminated many problems in the actuators such as production cost, mechanical complexity, and design algorithm. However, SA has complexities, such as predicting and monitoring behavior despite the many benefits. The first part of this paper deals with the prediction of SA behavior through mathematical models such as Ogden and Darijani, and its comparison with the results of experiments. At first, by examining different geometric models, the cubic structure was selected as the optimal structure in the investigated models. This geometrical structure at the same pressure showed the most significant bending in the simulation. The simulation results were then compared with experimental, and the final gripper model was designed and manufactured using a 3D printer with silicone rubber as for the polymer part. This geometrical structure is capable of bending up to a 90-degree angle at 70 kPa in less than 2 seconds. The second section is dedicated to monitoring the bending behavior created by the strain sensors with different sensitivity and stretchability. In the fabrication of the sensors, silicon is used as a soft material with hyperelastic behavior and carbon fiber as a conductive material in the soft material substrate. The SA designed in this paper is capable of deforming up to 1000 cycles without changing its characteristics and capable of moving objects weigh up to 1200 g. This SA has the capability of being used in soft robots and artificial hand making for high-speed objects harvesting.

Mapless Navigation Based on DQN Considering Moving Obstacles, and Training Time Reduction Algorithm (이동 장애물을 고려한 DQN 기반의 Mapless Navigation 및 학습 시간 단축 알고리즘)

  • Yoon, Beomjin;Yoo, Seungryeol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.3
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    • pp.377-383
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    • 2021
  • Recently, in accordance with the 4th industrial revolution, The use of autonomous mobile robots for flexible logistics transfer is increasing in factories, the warehouses and the service areas, etc. In large factories, many manual work is required to use Simultaneous Localization and Mapping(SLAM), so the need for the improved mobile robot autonomous driving is emerging. Accordingly, in this paper, an algorithm for mapless navigation that travels in an optimal path avoiding fixed or moving obstacles is proposed. For mapless navigation, the robot is trained to avoid fixed or moving obstacles through Deep Q Network (DQN) and accuracy 90% and 93% are obtained for two types of obstacle avoidance, respectively. In addition, DQN requires a lot of learning time to meet the required performance before use. To shorten this, the target size change algorithm is proposed and confirmed the reduced learning time and performance of obstacle avoidance through simulation.

Life Evaluation of Grease for Ball Bearings According to Temperature, Speed, and Load Changes (온도, 속도, 그리고 하중 변화에 따른 볼 베어링용 그리스의 수명평가)

  • Son, Jeonghoon;Kim, Sewoong;Choi, Byong Ho;Lee, Seungpyo
    • Tribology and Lubricants
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    • v.37 no.1
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    • pp.7-13
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    • 2021
  • Ball bearing is a device that supports and transmits a load acting on a rotating shaft, and it is a type of rolling bearings that uses the rolling friction of the balls by inserting balls between the inner ring and the outer ring. Grease, which is prepared by mixing a thickener with a base oil, is a lubricant commonly used in bearings and has the advantage of a simple structure and easy handling. Bearings are increasingly being used in high value-added products such as semiconductors, aviation, and robots in the era of the 4th industrial revolution. Accordingly, there is an increasing demand for bearing grease. The selection of grease is an important factor in the bearing design. Therefore, a study must be conducted on the grease life evaluation to select an appropriate grease according to operating conditions such as a high temperature, high rotational speed, and high load. In this study, we evaluate the life of ball-bearing grease according to various operating conditions, namely, temperature, speed, and load changes. For this, we develop and theoretically verify a grease life test machine for ball bearings. We conduct a life test of grease according to various operating conditions of bearings and predict the grease life with a 10% and 50% failure probability using the Weibull analysis. In addition, we analyze the oxide characteristics of the grease over time using the Fourier transform infrared spectroscopy and the deterioration characteristics of the grease using the carbonyl index.

How Does the Media Deal with Artificial Intelligence?: Analyzing Articles in Korea and the US through Big Data Analysis (언론은 인공지능(AI)을 어떻게 다루는가?: 뉴스 빅데이터를 통한 한국과 미국의 보도 경향 분석)

  • Park, Jong Hwa;Kim, Min Sung;Kim, Jung Hwan
    • The Journal of Information Systems
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    • v.31 no.1
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    • pp.175-195
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    • 2022
  • Purpose The purpose of this study is to examine news articles and analyze trends and key agendas related to artificial intelligence(AI). In particular, this study tried to compare the reporting behaviors of Korea and the United States, which is considered to be a leader in the field of AI. Design/methodology/approach This study analyzed news articles using a big data method. Specifically, main agendas of the two countries were derived and compared through the keyword frequency analysis, topic modeling, and language network analysis. Findings As a result of the keyword analysis, the introduction of AI and related services were reported importantly in Korea. In the US, the war of hegemony led by giant IT companies were widely covered in the media. The main topics in Korean media were 'Strategy in the 4th Industrial Revolution Era', 'Building a Digital Platform', 'Cultivating Future human resources', 'Building AI applications', 'Introduction of Chatbot Services', 'Launching AI Speaker', and 'Alphago Match'. The main topics of US media coverage were 'The Bright and Dark Sides of Future Technology', 'The War of Technology Hegemony', 'The Future of Mobility', 'AI and Daily Life', 'Social Media and Fake News', and 'The Emergence of Robots and the Future of Jobs'. The keywords with high centrality in Korea were 'release', 'service', 'base', 'robot', 'era', and 'Baduk or Go'. In the US, they were 'Google', 'Amazon', 'Facebook', 'China', 'Car', and 'Robot'.

Development of External Expansion Devices and Convergence Contents for Future Education based on Software Teaching Tools (소프트웨어 교육용 교구 활용 미래 교육을 위한 융합 콘텐츠 및 외부 확장장치 개발)

  • Ju, Yeong-Tae;Kim, Jong-Sil;Kim, Eung-Kon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.6
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    • pp.1317-1322
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    • 2021
  • Software in the era of the Fourth Industrial Revolution is becoming a key foundation in an intelligent information society. Therefore, it is necessary to study the new direction of manpower training and education that can cope with the times. To this end, the Ministry of Education reorganized the curriculum and is implementing software education based on a logical problem-solving process based on computing thinking skills rather than acquiring general ICT knowledge. However, there is a lack of securing high-quality educational content for software education, and there is also a lack of teaching aids that can be taught in connection with advanced IT technologies. To overcome this, this paper proposes the development of external expansion devices to expand educational content and functions capable of convergent software education such as artificial intelligence using coding robots for software education. Through this, effective software education is possible by improving the curriculum of the existing simple problem-solving method and developing various learning materials.

Design of Robot Arm for Service Using Deep Learning and Sensors (딥러닝과 센서를 이용한 서비스용 로봇 팔의 설계)

  • Pak, Myeong Suk;Kim, Kyu Tae;Koo, Mo Se;Ko, Young Jun;Kim, Sang Hoon
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.5
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    • pp.221-228
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    • 2022
  • With the application of artificial intelligence technology, robots can provide efficient services in real life. Unlike industrial manipulators that do simple repetitive work, this study presented design methods of 6 degree of freedom robot arm and intelligent object search and movement methods for use alone or in collaboration with no place restrictions in the service robot field and verified performance. Using a depth camera and deep learning in the ROS environment of the embedded board included in the robot arm, the robot arm detects objects and moves to the object area through inverse kinematics analysis. In addition, when contacting an object, it was possible to accurately hold and move the object through the analysis of the force sensor value. To verify the performance of the manufactured robot arm, experiments were conducted on accurate positioning of objects through deep learning and image processing, motor control, and object separation, and finally robot arm was tested to separate various cups commonly used in cafes to check whether they actually operate.

Artificial intelligence-based chatbot system for use in RCMS (RCMS에 활용하기 위한 인공지능 기반 챗봇 시스템)

  • Kim, Yongkuk;Kim, Sujin;Jung, Hoekyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.7
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    • pp.877-883
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    • 2021
  • Artificial intelligence technology is widely used in industrial and smart home fields such as manufacturing robots, artificial intelligence speakers, and robot vacuum cleaners. In this paper, we designed and implemented a 1:1 chatbot system based on artificial intelligence for use in RCMS (Real-time Cash Management System). The RCMS chatbot implemented in this paper was constructed with a total of 210 query scenarios in nine areas, including research expenses and system usage, based on 13,500 questions and answers from existing online bulletin boards. The chatbot is expected to solve the problem of insufficient number of counselors and to increase user satisfaction by responding to the researcher's inquiries after working hours, and the recommendation service for the cost of use, which had the most inquiries from researchers, reduces the number of consultations. It is expected to improve the quality of answers to other counseling inquiries.