• Title/Summary/Keyword: Core robot technology

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A Study on Current States and Required Technologies of Smart Speaker in Service Robot

  • Lee, Seong-Hoon;Lee, Dong-Woo
    • Journal of Advanced Information Technology and Convergence
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    • v.8 no.2
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    • pp.129-137
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    • 2018
  • Smart machines are one of the topics of our society recently. A smart machine should have a wiser or smarter function than the past. In the modern society, the environment of each family is being improved toward the direction of smart home. In this environment, smart speakers are now increasingly serving as interfaces for controlling various devices in the home, from devices that listen to conventional music. In this paper, we review the technology development trends of domestic and foreign smart speaker market, and describe the core technologies required. In Korea, while SKT and KT are dominant in the speaker market, major IT companies such as Amazon, Google and Apple are focusing on launching related products and technology development.

An algorithm of marking line correction for robot-based layout automation of building structures

  • Lim, Hyunsu;Kim, Taehoon;Cho, Kyuman;Kim, Taehoon;Kim, Chang-Won
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.312-318
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    • 2022
  • Robot-based layout automation has been recently promoted for the purpose of improving productivity and quality. Marking robots have various functional demands to secure marking precision and environmental adaptability. In particular, in order to automate marking work of building structure, correction of the marking line through position recognition of rebars placed is required. Because the rebars must maintain a constant cover thickness from the formwork surface, if the rebars are out of planned position, the rebar or marking line need to be corrected to secure the cover thickness. Thus, the marking robot for structural work needs to have the function for determining the position correction of the rebar or the marking line. In order to judge the correction of marking line, it is required to measure the distance between the planned marking line and the rebar placed. Therefore, this study proposes an algorithm that can measure the distance between the planned line and the rebar, and correct marking line for the automatic operation of the marking robot. The results of this study will be utilized as a core function for unmanned operation of the marking robot and contribute to securing precise marking by reflecting construction errors.

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A Study on the Failure Diagnosis of Transfer Robot for Semiconductor Automation Based on Machine Learning Algorithm (머신러닝 알고리즘 기반 반도체 자동화를 위한 이송로봇 고장진단에 대한 연구)

  • Kim, Mi Jin;Ko, Kwang In;Ku, Kyo Mun;Shim, Jae Hong;Kim, Kihyun
    • Journal of the Semiconductor & Display Technology
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    • v.21 no.4
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    • pp.65-70
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    • 2022
  • In manufacturing and semiconductor industries, transfer robots increase productivity through accurate and continuous work. Due to the nature of the semiconductor process, there are environments where humans cannot intervene to maintain internal temperature and humidity in a clean room. So, transport robots take responsibility over humans. In such an environment where the manpower of the process is cutting down, the lack of maintenance and management technology of the machine may adversely affect the production, and that's why it is necessary to develop a technology for the machine failure diagnosis system. Therefore, this paper tries to identify various causes of failure of transport robots that are widely used in semiconductor automation, and the Prognostics and Health Management (PHM) method is considered for determining and predicting the process of failures. The robot mainly fails in the driving unit due to long-term repetitive motion, and the core components of the driving unit are motors and gear reducer. A simulation drive unit was manufactured and tested around this component and then applied to 6-axis vertical multi-joint robots used in actual industrial sites. Vibration data was collected for each cause of failure of the robot, and then the collected data was processed through signal processing and frequency analysis. The processed data can determine the fault of the robot by utilizing machine learning algorithms such as SVM (Support Vector Machine) and KNN (K-Nearest Neighbor). As a result, the PHM environment was built based on machine learning algorithms using SVM and KNN, confirming that failure prediction was partially possible.

Technical Trend of Long-range Wireless Power Transfer (장거리 무선전력전송 기술동향)

  • Jung, Young-Bae
    • Journal of IKEEE
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    • v.22 no.1
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    • pp.216-222
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    • 2018
  • Long-range wireless power transmission technology goes beyond mere cell phones and small appliances, and is the core technology of 4'th industrial revolution such as robot, electric car, and IoT sensor network. In this paper, we will explore the evolution of long-range wireless power transmission technologies that have already become commercially available, with rapid advances in technology, beyond the traditional short-range technology that has become technologically common. Through this, it is intended to check the domestic research level and progress by identifying core technologies and technical challenge.

RFID-based access management robot (RFID를 이용한 출입관리 로봇)

  • Moon, Byung-Hyun;Lee, Tae-Hoon;Seo, Yong-Seok;Hwang, Ji-Young;Ryu, Jeong-Tak
    • Journal of Korea Society of Industrial Information Systems
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    • v.13 no.4
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    • pp.139-144
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    • 2008
  • RFID (Radio Frequency Identification) technology to create a ubiquitous society as a basis for the core technology-based and community-based technology, the development of technologies that go toward the new growth engines in Korea, one of the IT839 strategy is. This paper ubiquitous RFID technology to keep pace with the present management in society has developed a robot. The system is applied to the RFID cards by using the present management system to manage the personal attendance and reduce the hassle by installing a camera in a robot to prevent a proxy attendance, it added effect. In addition to the robot to determine the user's business to manage attendance, in addition to the menu over lunch with the correct time off work and out of business, and so the record companies and the lab is also possible to take full advantage of the system is introduced.

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Omni Camera Vision-Based Localization for Mobile Robots Navigation Using Omni-Directional Images (옴니 카메라의 전방향 영상을 이용한 이동 로봇의 위치 인식 시스템)

  • Kim, Jong-Rok;Lim, Mee-Seub;Lim, Joon-Hong
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.3
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    • pp.206-210
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    • 2011
  • Vision-based robot localization is challenging due to the vast amount of visual information available, requiring extensive storage and processing time. To deal with these challenges, we propose the use of features extracted from omni-directional panoramic images and present a method for localization of a mobile robot equipped with an omni-directional camera. The core of the proposed scheme may be summarized as follows : First, we utilize an omni-directional camera which can capture instantaneous $360^{\circ}$ panoramic images around a robot. Second, Nodes around the robot are extracted by the correlation coefficients of Circular Horizontal Line between the landmark and the current captured image. Third, the robot position is determined from the locations by the proposed correlation-based landmark image matching. To accelerate computations, we have assigned the node candidates using color information and the correlation values are calculated based on Fast Fourier Transforms. Experiments show that the proposed method is effective in global localization of mobile robots and robust to lighting variations.

Development of a deep learning-based cabbage core region detection and depth classification model (딥러닝 기반 배추 심 중심 영역 및 깊이 분류 모델 개발)

  • Ki Hyun Kwon;Jong Hyeok Roh;Ah-Na Kim;Tae Hyong Kim
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.6
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    • pp.392-399
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    • 2023
  • This paper proposes a deep learning model to determine the region and depth of cabbage cores for robotic automation of the cabbage core removal process during the kimchi manufacturing process. In addition, rather than predicting the depth of the measured cabbage, a model was presented that simultaneously detects and classifies the area by converting it into a discrete class. For deep learning model learning and verification, RGB images of the harvested cabbage 522 were obtained. The core region and depth labeling and data augmentation techniques from the acquired images was processed. MAP, IoU, acuity, sensitivity, specificity, and F1-score were selected to evaluate the performance of the proposed YOLO-v4 deep learning model-based cabbage core area detection and classification model. As a result, the mAP and IoU values were 0.97 and 0.91, respectively, and the acuity and F1-score values were 96.2% and 95.5% for depth classification, respectively. Through the results of this study, it was confirmed that the depth information of cabbage can be classified, and that it can be used in the development of a robot-automation system for the cabbage core removal process in the future.

Interaction Intent Analysis of Multiple Persons using Nonverbal Behavior Features (인간의 비언어적 행동 특징을 이용한 다중 사용자의 상호작용 의도 분석)

  • Yun, Sang-Seok;Kim, Munsang;Choi, Mun-Taek;Song, Jae-Bok
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.8
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    • pp.738-744
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    • 2013
  • According to the cognitive science research, the interaction intent of humans can be estimated through an analysis of the representing behaviors. This paper proposes a novel methodology for reliable intention analysis of humans by applying this approach. To identify the intention, 8 behavioral features are extracted from the 4 characteristics in human-human interaction and we outline a set of core components for nonverbal behavior of humans. These nonverbal behaviors are associated with various recognition modules including multimodal sensors which have each modality with localizing sound source of the speaker in the audition part, recognizing frontal face and facial expression in the vision part, and estimating human trajectories, body pose and leaning, and hand gesture in the spatial part. As a post-processing step, temporal confidential reasoning is utilized to improve the recognition performance and integrated human model is utilized to quantitatively classify the intention from multi-dimensional cues by applying the weight factor. Thus, interactive robots can make informed engagement decision to effectively interact with multiple persons. Experimental results show that the proposed scheme works successfully between human users and a robot in human-robot interaction.

Admittance Control for Satellite Docking Ground Testing System (위성 도킹 지상시험장치의 어드미턴스 제어)

  • Heejin Woo;Youngjin Choi;Daehee Won
    • The Journal of Korea Robotics Society
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    • v.19 no.1
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    • pp.71-78
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    • 2024
  • The paper presents a hardware-in-the-loop (HIL) system designed for satellite movement testing in the microgravity environment on the ground with two industrial robots. Especially, the paper deals with the contact between satellites during rendezvous and docking simulations of satellites using a robotic HILS system. For this purpose, the admittance control method plays a core role in preventing damage to the satellite or robot from contact force between satellites. The coordinate frames are transformed into the mass center of the satellite and the admittance control at the level of exponential coordinates is adopted to actively use the properties of Lie groups related to tracking errors. These methods effectively mitigate the risk of robot damage during inter-satellite contact and ensure efficient tracking performance of satellite movements.

Mechanism of Classification of IoT based Robot State in Smart Manufacturing Environment (스마트 제조 환경에서 IoT기반 로봇의 상태 분류방법에 대한 연구)

  • Kang, Hyun-chul;Han, Hyon-young;Bae, Hee-chul;Lee, Eun-seo;Son, Ji-yeon;Kim, Hyun;Kim, Young-kuk
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.742-743
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    • 2017
  • The smart factory market is expected to show high growth rate in the future, supported by demand for manufacturing innovation in order to overcome structural low growth. Especially in the future manufacturing industry, robots are combined with IT, becoming the most important core technology. In this paper, we proposed and implemented state information classification method for IoT-based robot control in smart manufacturing environment.

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