• The Journal of the Korea Contents Association
• /
• v.20 no.5
• /
• pp.79-89
• /
• 2020

The current study explored if users' self-relevance of the comparison domain with creative AI robot in music composition affected their envy toward the robot, cognitive assessment toward the music and intention toward working with robot in future. This study conducted a 2 (degree of self-relevance: high(college students majoring in music) vs. low(those not majoring in music) × 2 (working type: robot-only vs. robot-human collaboration) between-subjects factorial design experiment. The findings revealed that those majoring in music did not feel envious of the robot as much as those not majoring in music. However, compared to those not majoring in music, those majoring in music evaluated the robot's creativity lower, had more negative attitude toward the music, showed less intention to use the music and work with the robots in future. No interaction between the degree of self-relevance and the working type was found.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.52-54
• /
• 2021

With the advent of the era of artificial intelligence, robot education and teaching under its empowerment have been widely concerned and applied worldwide. The purpose of this study: systematically evaluate the application effect of AI educational robots in student education and teaching; the method of this study: use the computer to search for relevant education in the search tools such as "Web of Science", "CNKI", "ERIC", "IEEE" A comparative study of the effects of robot teaching and traditional teaching. The retrieval time is from January 2000 to January 2020. Comprehensive MetaAnalysis 2.0 was used for Meta analysis. The results of this study: A quantitative analysis of the 31 valid research literatures included, and an objective evaluation of the effect of the meta-analysis on AI educational robots. The analysis results show that the combined effect of AI educational robots on student learning effects is 0.465 This indicates that educational robots have a moderately positive effect on students 'learning effectiveness. The conclusion of this study: The application effect of AI educational robots in student education and teaching is better than traditional education methods, which can better promote student learning.

• The Journal of Korea Robotics Society
• /
• v.17 no.2
• /
• pp.198-208
• /
• 2022

In this paper, an autonomous driving system is implemented for the Segye AI Robot Race Competition that multiple vehicles drive simultaneously. By utilizing the ERP42-racing platform, RTK-GPS, and LiDAR sensors provided in the competition, we propose an autonomous driving system that can drive safely and quickly in a road environment with multiple vehicles. This system consists of a recognition, judgement, and control parts. In the recognition stage, vehicle localization and obstacle detection through waypoint-based LiDAR ROI were performed. In the judgement stage, target velocity setting and obstacle avoidance judgement are determined in consideration of the straight/curved section and the distance between the vehicle and the neighboring vehicle. In the control stage, adaptive cruise longitudinal velocity control based on safe distance and lateral velocity control based on pure-pursuit are performed. To overcome the limited experimental environment, simulation and partial actual experiments were conducted together to develop and verify the proposed algorithms. After that, we participated in the Segye AI Robot Race Competition and performed autonomous driving racing with verified algorithms.

• Journal of Korea Multimedia Society
• /
• v.25 no.8
• /
• pp.1049-1058
• /
• 2022

HAR(Human Action Recognition) such as anomaly and object detection has become a trend in research field(s) that focus on utilizing Artificial Intelligence (AI) methods to analyze patterns of human action in crime-ridden area(s), media services, and industrial facilities. Especially, in real-time system(s) using video streaming data, HAR has become a more important AI-based research field in application development and many different research fields using HAR have currently been developed and improved. In this paper, we propose and analyze a deep-learning-based HAR that provides more efficient scheme(s) using an intelligent AI models, such system can be applied to media services using RGB video streaming data usage without feature extraction pre-processing. For the method, we adopt Slowfast based on the Deep Neural Network(DNN) model under an open dataset(HMDB-51 or UCF101) for improvement in prediction accuracy.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.296-300
• /
• 1992

This paper deals with a dual mode control system design for the starching work robot. From the feature of this work, the robot has redundant degree of freedom. In this paper, we try to split the whole movement the robot into a gross motion part ai. a fine motion part so as to achieve a good tracking performance. The preview learning control is applied to the gross motion part. The validity of the dual mode control architecture is demonstrated.

• The Journal of Information Systems
• /
• v.31 no.1
• /
• pp.175-195
• /
• 2022

Purpose The purpose of this study is to examine news articles and analyze trends and key agendas related to artificial intelligence(AI). In particular, this study tried to compare the reporting behaviors of Korea and the United States, which is considered to be a leader in the field of AI. Design/methodology/approach This study analyzed news articles using a big data method. Specifically, main agendas of the two countries were derived and compared through the keyword frequency analysis, topic modeling, and language network analysis. Findings As a result of the keyword analysis, the introduction of AI and related services were reported importantly in Korea. In the US, the war of hegemony led by giant IT companies were widely covered in the media. The main topics in Korean media were 'Strategy in the 4th Industrial Revolution Era', 'Building a Digital Platform', 'Cultivating Future human resources', 'Building AI applications', 'Introduction of Chatbot Services', 'Launching AI Speaker', and 'Alphago Match'. The main topics of US media coverage were 'The Bright and Dark Sides of Future Technology', 'The War of Technology Hegemony', 'The Future of Mobility', 'AI and Daily Life', 'Social Media and Fake News', and 'The Emergence of Robots and the Future of Jobs'. The keywords with high centrality in Korea were 'release', 'service', 'base', 'robot', 'era', and 'Baduk or Go'. In the US, they were 'Google', 'Amazon', 'Facebook', 'China', 'Car', and 'Robot'.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.07a
• /
• pp.29-31
• /
• 2020

본 논문에서는 코로나19 사태로 인한 팬데믹(pandemic) 현상으로 인해 또래와 단절된 아동들의 정서발달을 위해 인공지능 낙서 로봇인 Doodle Robot을 제안한다. Doodle Robot은 또래 형제가 없는 아동에게 함께 그림을 그릴 수 있는 그림친구로서 아동의 정서적 발달에 기여한다. YOLO 알고리즘을 사용하여 객체검출기능을 구현하였고 낙서 Data는 Quick! Draw Dataset에서 추출하였다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.2
• /
• pp.333-336
• /
• 2020

AI-powered robot news is drawing attention as artificial intelligence technology is fully spread in the news distribution field. Robot news still has many technical and ethical problems, but academic research on this is insufficient. This study analyzes the issue of robot writing in artificial intelligent based robot journalism industry using SWOT analysis. As a result, the advantages of big data processes, accurate information gathering, high efficiency and disadvantages such as lack of independent arguments and lack of evidence and opportunities for technical development, government support, academic development, and industrial applications, and threats such as uncritical acceptance and lack of talent have been found. This study suggests three future-oriented directions, such as human-machine collaboration, intelligent news, and chat-bot, through previous studies on the development direction of robot journalism-based article writing.

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

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.11a
• /
• pp.349-350
• /
• 2022

Recently, AI (Artificial Intelligence) has been applied to various technologies such as automatic driving, robot and smart communication. Currently, AI system is developed by software-based method using tensor flow, and GPU (Graphic Processing Unit) is employed for processing unit. In this work, we developed an FPGA-based (Field Programmable Gate Array) AI system , and report on image recognition system to realize the AI system.