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The Study of Servo-Parameter Tuning Technique for 6-Axes Articulated Robot Manipulator in Consideration of Dynamic Characteristics (동적 특성을 고려한 6축 로봇의 서보 파라미터 튜닝에 관한 연구)

  • Chung, W.J.;Kim, H.G.;Lee, C.M.;Hong, D.S.;Park, S.G.;Seo, Y.G.;Lee, G.S.
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.16 no.5
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    • pp.1-6
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    • 2007
  • This paper presents a new experimental Servo-Parameter tuning technique for a 6-axes articulated robot manipulator, especially considering robot's dynamics. First of all, investigation for proportional gain of velocity control loop by using a Dynamic Signal Analyzer(DSA) is performed. Using the FUNCTION characteristic of DSA based on the Bode plot, the Bode plot of open loop transfer function can be obtained. In turn, the integral gain of a servo controller can be found out by using the integration time constant extracted from the Bode plot of open loop transfer function. In the meanwhile, the positional gain of the servo controller can be obtained by using the Bode plot of the closed loop transfer function. Using the experimental gain tuning technique proposed in this paper, the testing linear motion of DR6-II robot has been shown to be more accurate rather than the motion with a conventional(empirical) gain tuning technique in Doosan Mecatec Co., Ltd., by improving the dynamic response of the robot as well as synchronizing each joint velocity according to the positional command of an end-effector.

A Study on Vulnerability of Cyber Electronic Warfare and Analysis of Countermeasures for swarm flight of the NBC Reconnaissance Drones (화생방 정찰 드론의 군집비행 시 사이버전자전 취약점 및 대응방안 분석)

  • Kim, Jee-won;Park, Sang-jun;Lee, Kwang-ho;Jung, Chan-gi
    • Convergence Security Journal
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    • v.18 no.2
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    • pp.133-139
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    • 2018
  • The 5 Game changer means the concepts of the army's operation against the enemy's asymmetric threats so that minimize damage to the public and leads to victory in war in the shortest time. A study of network architecture of Dronebot operation is a key study to carry out integrated operation with integrated C4I system by organically linking several drones battle groups through ICT. The NBC reconnaissance drones can be used instead of vehicles and humans to detect NBC materials and share situations quickly. However, there is still a lack of research on the swarm flight of the NBC reconnaissance drones and the weaknesses of cyber electronic warfare. In this study, we present weaknesses and countermeasures of CBRNs in swarm flight operations and provide a basis for future research.

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The Development of Game Simulator for Snowboard (스노우보드 게임 시뮬레이터 개발)

  • Kim, Dong-Jin;Yoon, Pyoung-Won
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.4
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    • pp.510-516
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    • 2019
  • In this paper, a snowboard simulator that measures the user's motion and makes the user feel physical changes and enjoy actual snowboarding was developed. The speed and direction of the snowboard are determined by the user's center of gravity. The developed simulator is equipped with four springs on the snowboard plate, so that the slope can change according to the change in the user's weight center and be felt directly. The slope due to the change in the center of gravity of the user is measured using a three-axis acceleration sensor. The friction of the slope generated by the rotation of the snowboard is made possible by the user using the BLDC motor, and the rotation of the snowboard is measured using the hole sensor. For rapid data processing of the simulator, two MCUs are used to transfer the measured data to the PC using the acceleration sensor and motor separately. The developed simulator can experience slopes and friction of the slope directly, and wear measured data and HMD to enjoy more realistic snowboarding.

Animation and Machines: designing expressive robot-human interactions (애니메이션과 기계: 감정 표현 로봇과 인간과의 상호작용 연구)

  • Schlittler, Joao Paulo Amaral
    • Cartoon and Animation Studies
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    • s.49
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    • pp.677-696
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    • 2017
  • Cartoons and consequently animation are an effective way of visualizing futuristic scenarios. Here we look at how animation is becoming ubiquitous and an integral part of this future today: the cybernetic and mediated society that we are being transformed into. Animation therefore becomes a form of speech between humans and this networked reality, either as an interface or as representation that gives temporal form to objects. Animation or specifically animated films usually are associated with character based short and feature films, fiction or nonfiction. However animation is not constricted to traditional cinematic formats and language, the same way that design and communication have become treated as separate fields, however according to $Vil{\acute{e}}m$ Flusser they aren't. The same premise can be applied to animation in a networked culture: Animation has become an intrinsic to design processes and products - as in motion graphics, interface design and three-dimensional visualization. Video-games, virtual reality, map based apps and social networks constitute layers of an expanded universe that embodies our network based culture. They are products of design and media disciplines that are increasingly relying on animation as a universal language suited to multi-cultural interactions carried in digital ambients. In this sense animation becomes a discourse, the same way as Roland Barthes describes myth as a type of speech. With the objective of exploring the role of animation as a design tool, the proposed research intends to develop transmedia creative visual strategies using animation both as narrative and as an user interface.

Detection of Zebra-crossing Areas Based on Deep Learning with Combination of SegNet and ResNet (SegNet과 ResNet을 조합한 딥러닝에 기반한 횡단보도 영역 검출)

  • Liang, Han;Seo, Suyoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.3
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    • pp.141-148
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    • 2021
  • This paper presents a method to detect zebra-crossing using deep learning which combines SegNet and ResNet. For the blind, a safe crossing system is important to know exactly where the zebra-crossings are. Zebra-crossing detection by deep learning can be a good solution to this problem and robotic vision-based assistive technologies sprung up over the past few years, which focused on specific scene objects using monocular detectors. These traditional methods have achieved significant results with relatively long processing times, and enhanced the zebra-crossing perception to a large extent. However, running all detectors jointly incurs a long latency and becomes computationally prohibitive on wearable embedded systems. In this paper, we propose a model for fast and stable segmentation of zebra-crossing from captured images. The model is improved based on a combination of SegNet and ResNet and consists of three steps. First, the input image is subsampled to extract image features and the convolutional neural network of ResNet is modified to make it the new encoder. Second, through the SegNet original up-sampling network, the abstract features are restored to the original image size. Finally, the method classifies all pixels and calculates the accuracy of each pixel. The experimental results prove the efficiency of the modified semantic segmentation algorithm with a relatively high computing speed.