• Title/Summary/Keyword: Mobile Manipulation

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A Design of the Smart Control System for Industrial Automation Equipment (산업용 자동화 장비를 위한 스마트 제어 시스템 설계)

  • Kim, Bo-Hun;Kim, Hwang-Rae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.4
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    • pp.677-684
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    • 2017
  • Smart devices are used in a variety of industries, because applications for them are easy to develop and portable. However, industrial equipment can cause security problems for information and accidents when controlling the actuator of the equipment at a remote location. In this paper, we studied methods of solving these problems and the advantages of applying smart control systems to industrial equipment. We propose a manual manipulation method using queries and a smart control access procedure for controlling equipment using a smart device. In addition, we propose a data transmission method employing multiple encryption protocols and a user authentication method using unique information from the smart device and Q & A as the communication data protection and user authentication methods, respectively. In order to evaluate its performance, an operation test of the smart control system and user authentication comparison experiment were performed. In order to understand the advantages of applying the smart control system to the equipment, we conducted a comparative experiment with a teach pendant and evaluated its reaction time in case of error.

Design and Development of Multiple Input Device and Multiscale Interaction for GOCI Observation Satellite Imagery on the Tiled Display (타일드 디스플레이에서의 천리안 해양관측 위성영상을 위한 다중 입력 장치 및 멀티 스케일 인터랙션 설계 및 구현)

  • Park, Chan-Sol;Lee, Kwan-Ju;Kim, Nak-Hoon;Lee, Sang-Ho;Seo, Ki-Young;Park, Kyoung Shin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.3
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    • pp.541-550
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    • 2014
  • This paper describes a multi-scale user interaction based tiled display visualization system using multiple input devices for monitoring and analyzing Geostationary Ocean Color Imager (GOCI) observation satellite imagery. This system provides multi-touch screen, Kinect motion sensing, and moblie interface for multiple users to control the satellite imagery either in front of the tiled display screen or far away from a distance to view marine environmental or climate changes around Korean peninsular more effectively. Due to a large amount of memory required for loading high-resolution GOCI satellite images, we employed the multi-level image load technique where the image was divided into small tiled images in order to reduce the load on the system and to be operated smoothly by user manipulation. This system performs the abstraction of common input information from multi-user Kinect motion and gestures, multi-touch points and mobile interaction information to enable a variety of user interactions for any tiled display application. In addition, the unit of time corresponding to the selected date of the satellite images are sequentially displayed on the screen and multiple users can zoom-in/out, move the imagery and select buttons to trigger functions.

Effective Utilization of Domain Knowledge for Relational Reinforcement Learning (관계형 강화 학습을 위한 도메인 지식의 효과적인 활용)

  • Kang, MinKyo;Kim, InCheol
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.3
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    • pp.141-148
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    • 2022
  • Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

A study on security independent behavior in social game using expanded health belief model (건강신념모델을 확장한 소셜게임(Social Game) 보안의지행동에 관한 연구)

  • Ahn, Ho-Jeong;Kim, Sung-Jun;Kwon, Do-Soon
    • Management & Information Systems Review
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    • v.35 no.2
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    • pp.99-118
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    • 2016
  • With the development of Internet and popularization of smartphones over recent years, social network services are experiencing rapid growth. On top of this, smartphone gaming market is showing a rapid growth and the use of mobile social games is on the significant rise. The occurrence of game data manipulation targeting these services and personal information leakage is highlighting the importance of social gaming security. This study is intended to propose development plans effective and efficient in social game services by figuring out factors putting effects on security dependent behavior of social game users in Korea and carrying out a practical study on the casual relationship between factors influencing security dependent behavior through recognized behavioral control and attitudes for privacy infringement of these factors. To do this, proposed was a study model in which the HBM(Health Belief Model) allowing the social game user to influence security dependent behavior was expanded and applied as a major variable. To verify the study model of this study practically, a survey was conducted among university students in Seoul-based K University and S University who had experienced using social game services. According to the study findings, firstly, the perceived seriousness turned out to provide positive influence to trust. But, the perceived seriousness turned out not to put positive effects on self-efficacy. Secondly, the perceived probability turned out not to put positive effects on self-efficacy and trust. Thirdly, the perceived gain turned out to put positive effects on self-efficacy and trust. Fourthly, the perceived disorder turned out not to put positive effects on self-efficacy and trust. Fifthly, self-efficacy turned out to put positive effects on trust. But, self-efficacy turned out not to put positive effects on security dependent behavior. Sixthly, trust turned out not to put positive effects on security dependent behavior. This study is intended to make a strategic proposal so that social game users can raise awareness of their level of security perception and security willingness through this.

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