• Convergence Security Journal
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• v.17 no.2
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• pp.153-158
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• 2017

The robot imitates humans and recognizes the external environment and judges the situation. The robot is a machine that operates autonomously. Robots are divided into manufacturing robots and service robots. Service robots are classified as professional service robots and personal service robots. Because of the intensified competition of productivity in manufacturing industries, rising safety issues, low birth rate and aging, the robots industry is emerging. Recently, the robot industry is a complex of advanced technology fields, and it is attracting attention as a new industry where innovation potential and growth potential are promising. IT, BT, and NT related elements are fused and implemented, and the ripple effect is very large. Due to changes in social structure and life patterns, social interest in life extension and health is increasing. There is much interest in the medical field. Now the artificial intelligence (AI) industry is growing rapidly. It is necessary to secure global competitiveness through strengthening cooperation between large and small companies. We must combine R&D investment capability and marketing capability, which are advantages of large corporations, and robotic technology. We need to establish a cooperative model and secure global competitiveness through M&A.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.771-778
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• 2004

Recently, various applications of robot system become more popular in accordance with rapid development of computer hardware/software, artificial intelligence, and automatic control technology. Formerly robots mainly have been used in industrial field, however, nowadays it is said that the robot will do an important role in the home service application. To make the robot more useful, we require further researches on implementation of natural communication method between the human and the robot system, and autonomous behavior generation. The gesture recognition technique is one of the most convenient methods for natural human-robot interaction, so it is to be solved for implementation of intelligent robot system. In this paper, we describe the state-of-the-art of advanced gesture recognition technologies for intelligent robots according to three methods; sensor based method, feature based method, appearance based method, and 3D model based method. And we also discuss some problems and real applications in the research field.

• The Journal of Korean Association of Computer Education
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• v.22 no.4
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• pp.35-45
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• 2019

How future generations perceive coexistence with intelligent robots is an important element of how SW and artificial intelligence education should be designed and conducted. This study conducted a survey of 214 first graders in middle school and looked at differences in understanding and perception of coexistence through empathy and expected problem situations depending on the type of intelligent robot. As a result of the analysis, Firstly, if the form was not explicit, it was recognized as a top-down relationship, and Second, in the case of human form, it was ready to recognize intelligent robots and communicate with them. Third, Many people were feeling Emotion in the Robot shape AI. Fourth, there was a vague sense of uneasiness about simple mechanical robots. The study is meaningful as a case study to confirm awareness of intelligent robots and needs to consider and establish awareness of whether they can coexist and live together with robots by age group as well as middle school students.

• The Journal of Bigdata
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• v.7 no.1
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• pp.37-47
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• 2022

Autonomous delivery operation data is the key to driving a paradigm shift for last-mile delivery in the Corona era. To bridge the technological gap between domestic autonomous delivery robots and overseas technology-leading countries, large-scale data collection and verification that can be used for artificial intelligence training is required as the top priority. Therefore, overseas technology-leading countries are contributing to verification and technological development by opening AI training data in public data that anyone can use. In this paper, 326 objects were collected to trainn autonomous delivery robots, and artificial intelligence models such as Mask r-CNN and Yolo v3 were trained and verified. In addition, the two models were compared based on comparison and the elements required for future autonomous delivery robot research were considered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1466-1488
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• 2022

Recently, the importance and necessity of artificial intelligence (AI), especially machine learning, has been emphasized. In fact, studies are actively underway to solve complex and challenging problems through the use of AI systems, such as intelligent CCTVs, intelligent AI security systems, and AI surgical robots. Information security that involves analysis and response to security vulnerabilities of software is no exception to this and is recognized as one of the fields wherein significant results are expected when AI is applied. This is because the frequency of malware incidents is gradually increasing, and the available security technologies are limited with regard to the use of software security experts or source code analysis tools. We conducted a study on MalDC, a technique that converts malware into images using machine learning, MalDC showed good performance and was able to analyze and classify different types of malware. MalDC applies a preprocessing step to minimize the noise generated in the image conversion process and employs an image augmentation technique to reinforce the insufficient dataset, thus improving the accuracy of the malware classification. To verify the feasibility of our method, we tested the malware classification technique used by MalDC on a dataset provided by Microsoft and malware data collected by the Korea Internet & Security Agency (KISA). Consequently, an accuracy of 97% was achieved.

• Smart Media Journal
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• v.11 no.7
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• pp.94-103
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• 2022

Weeds bring disadvantages to crops since they can damage them, and a clean treatment with less pollution and contamination should be developed. Artificial intelligence gives new hope to agriculture to achieve smart farming. This study delivers an automated weeds growth point detection using deep learning. This study proposes a combination of semantic graphics for generating data annotation and U-Net with pre-trained deep learning as a backbone for locating the growth point of the weeds on the given field scene. The dataset was collected from an actual field. We measured the intersection over union, f1-score, precision, and recall to evaluate our method. Moreover, Mobilenet V2 was chosen as the backbone and compared with Resnet 34. The results showed that the proposed method was accurate enough to detect the growth point and handle the brightness variation. The best performance was achieved by Mobilenet V2 as a backbone with IoU 96.81%, precision 97.77%, recall 98.97%, and f1-score 97.30%.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.23-30
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• 2024

This paper studies a GPS error filtering method that takes into account the continuity of the ongoing path to enhance the safety of autonomous agricultural mobile robots. Real-Time Kinematic Global Positioning System (RTK-GPS) is increasingly utilized for robot position evaluation in outdoor environments due to its significantly higher reliability compared to conventional GPS systems. However, in orchard environments, the robot's current position obtained from RTK-GPS information can become unstable due to unknown disturbances like orchard canopies. This problem can potentially lead to navigation errors and path deviations during the robot's movement. These issues can be resolved by filtering out GPS information that deviates from the continuity of the waypoints traversed, based on the robot's assessment of its current path. The contributions of this paper is as follows. 1) The method based on the previous waypoints of the traveled path to determine the current position and trajectory. 2) GPS filtering method based on deviations from the determined path. 3) Finally, verification of the navigation errors between the method applying the error filter and the method not applying the error filter.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.855-858
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• 2003

The trends of recent developed a pet robot which interacts with people are increased gradually. There are a few pet robots that are a robot dog, robot cat, and robot fish. The pet robot is featured that it is possible to sympathize and give pleasure to human. The pet robots express delight, sorrow, surprise, and hunger through the artificial intelligence. Previously, the pet robot has to exchange the battery when it is exhausted. Commercialized robots have a self-recharging function, which express hunger. Robot dog AIBO, SONY in Japan, checks the battery for expressing hunger. They find an energy station for recharge. While operation time of AIBO is 1 hour 30 minutes, recharging time is 2 hours. Recharging time is longer than operation time. During the recharge, they don't operate. We obtain a motivation for eating the battery when find the problem. In this paper, introduce an Autonomous Eating Pet Robot and propose a design for realization. The Autonomous Eating Pet Robot has a function that is the most basic instinct that is finding a food and evacuating.

• Korean Journal of Computational Design and Engineering
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• v.12 no.1
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• pp.50-57
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• 2007

In recent years, many robotics researches have been focused on developing human-friendly robots, that is, humanoid biped robots. The researches of humanoid robots include various areas such as hardware development, control of biped locomotion, artificial intelligence, human interaction, etc. The present work concerns the hardware development of a mid-size humanoid robot, BONOBO, focusing on rapid development of outer body parts with integrated application if CAD/CAM/CAE/RP. Most parts are three-dimensionally designed using 3D CAD, and effectively connected with CAE analyses using both kinematic simulation and structural analysis. In order to reduce lead time and investment cost for parts developments, Rapid Prototyping (RP) and CAM are selectively utilized for manufacturing body parts. These master parts are then replicated using the vacuum casting process, from which we can obtain plastic parts repeatedly. Through this integrated approach, the first prototype of BONOBO can be successfully developed with relatively low time and investment costs.

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.163-169
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• 2019

Robot ALICE@ERICA is a service robot developed to receive donations and to provide information services. ALICE@ERICA stands for Artificial Learning Intelligence robot for Culture and Entertainment at ERICA. In order to achieve the specific purpose of receiving donations, proper appearance design, appropriate movement and good communication skills are required in terms of HRI. In this paper, we introduce three strategies for developing robots to receive donations effectively. The first is to design a robot that makes people feel intimacy, the second is to approach only one of several people as a donor, and finally the donor communicates with video contents and voice recognition. A survey was conducted on the person who showed the reaction after the robot donated money in public places. Based on the survey results, it is proved that the method presented in this study effectively contributed to fund raising. If robots can perform actions that require high level of HRI, such as donation, robots can contribute more to human society. We hope that this study contributes to the improvement of human happiness.