• Journal of Industrial Convergence
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• v.20 no.11
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• pp.127-134
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• 2022

With the recent advent of the Fourth Industrial Revolution, the importance of the platform business is increasing. Most global companies with high market value are known as platform companies. This change is changing the business model of companies in various industries. However, existing studies have mainly focused on information-intensive industries and large companies. Therefore, this study attempted to analyze the case of Everybot, which is successfully growing in the service robot industry. Everybot is known as a company that produces robot cleaners. However, according to the result, the company has focused on developing autonomous driving technologies and pursuing platform-based business strategies rather than product-based ones. The results of this study have theoretical and practical implications by showing how domestic small and medium-sized robot companies apply platform-based business strategies to achieve long-term growth with gaining leadership in the personal service robotics market.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2123-2130
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• 2015

For such automatic monitoring robot or a robot cleaner that is utilized indoors, if it deviates from someone by replacement or, or of a mobile robot such as collisions with unexpected object direction or planned path, based on the planned path There is a need to come back to, it is necessary to tough self-position estimation ability of mobile robot in this, which is also associated with resolution of the kidnap problem of conventional mobile robot. In this study, the case of a mobile robot, operates indoors, you want to take advantage of the low cost of the robot. Therefore, in this paper, by using the acquisition device to an external image information such as the CCTV which is installed in a room, it acquires the environment image and take advantage of marker recognition of the mobile robot at the same time and converted it absolutely spatial coordinates it is, we are trying to solve the self-position estimation of the mobile robot in the room and kidnap problem and actual implementation methods potential field to try utilizing robotic systems. Thus, by implementing the method proposed in this study to the actual robot system, and is promoting the relevant experiment was to verify the results.

• Proceedings of the KIPE Conference
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• 2015.11a
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• pp.23-24
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• 2015

청소 능력을 향상시키기 위해 높은 출력을 갖는 흡입 모터를 탑재한 로봇 청소기의 경우 계통에 연결하여 동작하는 유선 모드와 계통과 분리되어 무선 모드로 동작이 가능하다. 고출력 모터를 구동하기 위하여 듀얼 모드 로봇 청소기는 고용량의 배터리가 필요하고, 그에 따라 배터리 충전기의 용량 또한 증가되어야 한다. 본 논문에서는 듀얼 모드 로봇청소기의 동작 모드를 분석하여 유/무선 동작 및 배터리 충전이 가능한 800W급 전력 변환 장치를 개발하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1375-1377
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• 2015

초음파센서와 광학먼지센서를 이용하여 라즈베리파이 청소기를 제작하였다. 블루투스 통신을 통해 로봇청소기의 움직임을 제어하고, 초음파센서를 활용하여 장애물의 위치를 파악하며, 광학먼지센서를 이용하여 먼지농도를 파악한 후 이를 활용하여 청소알고리즘을 구현한다. 라즈베리파이와 아두이노를 사용하여 기존의 로봇청소기와는 다른 광학먼지센서를 활용한 개선된 알고리즘 방식으로 로봇청소기를 제어하여 청소의 효율성을 높여주는 효과가 있다.

• Electronics and Telecommunications Trends
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• v.35 no.3
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• pp.1-8
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• 2020

Artificial-intelligence (AI) technology is used in a variety of fields, from robot cleaner motion control to call center counselors, AI speakers, and Mars exploration. Because the technology levels of all applications and services that utilize AI vary widely, it is not possible to view all applications using AI technology at the same level. Nevertheless, there have been no cases in which the level of AI technology was defined. Therefore, the Electronics and Telecommunications Research Institute (ETRI) Artificial Intelligence Research Laboratory has defined the levels of the main technical elements of AI from steps 1 to 6. In this report, the Artificial Intelligence Technology Level 1.0 (ATL 1.0) is presented. It was established by comprehensively referring to the AI technology prospects and technology roadmaps of major countries. It is hoped that it can be used as a measure for determining the levels of AI applications or services or as an indicator for establishing a technology roadmap.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.17-29
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• 2017

IRecently, researches on the recognition of indoor user situations through various sensors in a smart home environment are under way. In this paper, the case study was conducted to determine the operation of the robot vacuum cleaner by inferring the user 's indoor situation through the operation of home appliances, because the indoor situation greatly affects the operation of home appliances. In order to collect learning data for indoor situation awareness model learning, we received feedbacks from user when there was a mistake about the cleaning situation. In this paper, we propose a semi-supervised learning method using user feedback data. When we receive a user feedback, we search for the labels of unlabeled data that most fit the feedbacks collected through genetic algorithm, and use this data to learn the model. In order to verify the performance of the proposed algorithm, we performed a comparison experiments with other learning algorithms in the same environment and confirmed that the performance of the proposed algorithm is better than the other algorithms.

• The Journal of Information Systems
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• v.32 no.3
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• pp.133-150
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• 2023

Purpose This study aims to develop classification models using a decision tree algorithm to identify core keywords and rules influencing online consumer review evaluations for the robot vacuum cleaner on Amazon.com. The difference from previous studies is that we analyze core keywords that affect the evaluation results by dividing the subjects that evaluate online consumer reviews into self-evaluation (star ratings) and peer evaluation (helpfulness votes). We investigate whether the core keywords influencing star ratings and helpfulness votes vary across different products and whether there is a similarity in the core keywords related to star ratings or helpfulness votes across all products. Design/methodology/approach We used random under-sampling to balance the dataset. We progressively removed independent variables based on decreasing importance through backwards elimination to evaluate the classification model's performance. As a result, we identified classification models that best predict star ratings and helpfulness votes for each product's online consumer reviews. Findings We have identified that the core keywords influencing self-evaluation and peer evaluation vary across different products, and even for the same model or features, the core keywords are not consistent. Therefore, companies' producers and marketing managers need to analyze the core keywords of each product to highlight the advantages and prepare customized strategies that compensate for the shortcomings.