• Title/Summary/Keyword: AI Robot

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AI baby mobile to prevent infant suffocation deaths (유아 질식사 예방 AI 아기 모빌)

  • Ye-Hun Jeong;Ji-Yeoing Cheon;Jeong-hwan Lee;Dong-Min kim;Do-Yoon Kim;Hyun-Don Kim
    • Annual Conference of KIPS
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    • 2023.11a
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    • pp.992-993
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    • 2023
  • 본 논문은 유아 질식사 사고를 예방하고 유아의 안전을 증진하기 위해 인공 지능(AI)을 활용한 아기 모빌의 개발과 적용에 관한 연구를 제시한다. 유아 뒤집기로 인한 사고는 아기의 안전에 심각한 위험을 초래하며, 이러한 사고를 예방하기 위한 새로운 접근 방식으로 AI 기술을 도입하는 것을 목표로 하였다. 본 연구에서는 AI 기술을 이용한 아기 모빌의 설계, 개발, 및 효과적인 적용 방안을 논의하며, 이를 통해 유아의 안전을 강화하고 부모들에게 편의성을 제공하는 방안을 제안했다.

A Study on hotel AI robot service built on the value-attitude-behavior(VAB) model (가치-태도-행동 모델을 적용한 호텔 AI 로봇서비스에 관한 연구)

  • Hejin Chun;Heeseung Lee
    • Smart Media Journal
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    • v.12 no.8
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    • pp.60-68
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    • 2023
  • After COVID-19, hotel industry is rapidly experiencing changes in the business environment, and under the influence of the Fourth Industrial Revolution, hotel industry is striving to secure competitive advantages through differentiation, including the use of big data and the IoT in service provision, as well as the introduction of artificial intelligence(AI) robot services. This study analyzed the perceived value of AI robot services and their impact on usage attitudes and behavioral intentions of customers who have used hotels that have introduced AI robot services. The results of the study showed that the value of robot services perceived by customers who have used robot services in hotels is categorized into three dimensions: social, experiential, and functional, and all of them have a positive effect on usage attitudes, with social, functional, and experiential values having a positive effect on usage attitudes in that order. Attitude toward use was also analyzed to have a positive effect on behavioral intention, which is consistent with the value-attitude-behavior model. Therefore, it is necessary for hotels to improve the satisfaction of hotel guests through diversified services of AI robot service.

Battle Simulator for Multi-Robot Mission Simulation and Reinforcement Learning (다중로봇 임무모의 및 강화학습을 위한 전투급 시뮬레이터 연구)

  • Jungho Bae;Youngil Lee;Dohyun Kim;Heesoo Kim;Myoungyoung Kim;Myungjun Kim;Heeyoung Kim
    • Journal of the Korea Institute of Military Science and Technology
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    • v.27 no.5
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    • pp.619-627
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    • 2024
  • As AI technology advances, interest in performing multi-robot autonomous missions for manned-unmanned teaming (MUM-T) is increasing. In order to develop autonomous mission performance technology for multiple robots, simulation technology that reflects the characteristics of real robots and can flexibly apply various missions is needed. Additionally, in order to solve complex non-linear tasks, an API must be provided to apply multi-robot reinforcement learning technology, which is currently under active research. In this study, we propose the campaign model to flexibly simulate the missions of multiple robots. We then discuss the results of developing a simulation environment that can be edited and run and provides a reinforcement learning API including acceleration performance. The proposed simulated control module and simulated environment were verified using an enemy infiltration scenario, and parallel processing performance for efficient reinforcement learning was confirmed through experiments.

Blockchain-Based Juridical AI Registration System (블록체인 기반 AI 법인 등록제)

  • Jeon, MinGyu;Hwang, Chiyeon;Na, Hyeon-Suk
    • Journal of Digital Convergence
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    • v.18 no.5
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    • pp.17-23
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    • 2020
  • With the advancement of AI technology, legal status and regulation issues for AI robots, and the necessity of a robot registration system are emerging. Since the shape and activity area of AI robots will no longer be limited to hardware in one country, the definition and regulation of AI robots should be expanded to a comprehensive concept including software, and information about them should be securely managed and shared by governments around the world. From this perspective, we extend 'AI robot' to the concept of Juridical AI encompassing hardware and software, and propose a method to operate the Juridical AI registration system using a permissioned blockchain called Juridical AI Chain. Since blockchain is an internationally distributed database, operating such AI registration system based on the blockchain will be a way to effectively cope with the global problems caused by the commercialization of AI robots.

Development of Quadruped Walking Robot AiDIN for Dynamic Walking (동적보행을 위한 생체모방형 4족 보행로봇 AiDIN의 개발)

  • Kang, Tae-Hun;Song, Hyun-Sup;Koo, Ig-Mo;Choi, Hyouk-Ryeol
    • The Journal of Korea Robotics Society
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    • v.1 no.2
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    • pp.203-211
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    • 2006
  • In this research, a comprehensive study is performed upon the design of a quadruped walking robot. In advance, the walking posture and skeletal configuration of the vertebrate are analyzed to understand quadrupedal locomotion, and the roles of limbs during walking are investigated. From these, it is known that the forelimbs just play the role of supporting their body and help vault forward, while most of the propulsive force is generated by hind limbs. In addition, with the study of the stances on walking and energy efficiency, design criteria and control method for a quadruped walking robot are derived. The proposed controller, though it is simple, provides a useful framework for controlling a quadruped walking robot. In particular, introduciton of a new rhythmic pattern generator relieves the heavy computational burden because it does not need any computation on kinematics. Finally, the proposed method is validated via dynamic simulations and implementing in a quadruped walking robot, called AiDIN(Artificial Digitigrade for Natural Environment).

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Design and Development of Modular Replaceable AI Server for Image Deep Learning in Social Robots on Edge Devices (엣지 디바이스인 소셜 로봇에서의 영상 딥러닝을 위한 모듈 교체형 인공지능 서버 설계 및 개발)

  • Kang, A-Reum;Oh, Hyun-Jeong;Kim, Do-Yun;Jeong, Gu-Min
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.6
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    • pp.470-476
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    • 2020
  • In this paper, we present the design of modular replaceable AI server for image deep learning that separates the server from the Edge Device so as to drive the AI block and the method of data transmission and reception. The modular replaceable AI server for image deep learning can reduce the dependency between social robots and edge devices where the robot's platform will be operated to improve drive stability. When a user requests a function from an AI server for interaction with a social robot, modular functions can be used to return only the results. Modular functions in AI servers can be easily maintained and changed by each module by the server manager. Compared to existing server systems, modular replaceable AI servers produce more efficient performance in terms of server maintenance and scale differences in the programs performed. Through this, more diverse image deep learning can be included in robot scenarios that allow human-robot interaction, and more efficient performance can be achieved when applied to AI servers for image deep learning in addition to robot platforms.

Human-Robot Interaction by Mobile Device for Intelligence Robot (모바일 기기를 통한 지능형 로봇의 인간-로봇 상호작용)

  • Choi, Byung-Gi;Kwag, Byul-Sem;Park, Chun-Sung;Lee, Jae-Ho
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06b
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    • pp.43-46
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    • 2010
  • 지능형 로봇의 인간-로봇 상호작용(Human-Robot Interaction)은 현재 세계적으로 주목받는 연구 분야 중 하나이다. 이 논문에서는 지능형 로봇의 작업 완결성을 높이기 위한 방편의 일환으로 사용자에게 작업 내용을 공개하고, 문제 발생 시 사용자의 개입을 유도하는 형태의 인간-로봇 상호작용을 제안한다. 이러한 형태의 서비스는 지능형 로봇이 작업 수행 중 필요한 경우 사용자의 선택 통해 예상치 못한 상황에 대해 유연한 대처를 할 수 있으며, 동시에 로봇의 현재 상황을 사용자가 확인할 수 있도록 하는 수단을 제공한다. 이를 위해 이 논문은 Android 플랫폼과 로봇 간의 로봇-사용자 정보교환을 구현하고, 나아가 범용적이고 일반적인 인간-로봇 상호작용을 위한 연구방향을 제시하고자 한다.

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Voice Command-based Prediction and Follow of Human Path of Mobile Robots in AI Space

  • Tae-Seok Jin
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.2_1
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    • pp.225-230
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    • 2023
  • This research addresses sound command based human tracking problems for autonomous cleaning mobile robot in a networked AI space. To solve the problem, the difference among the traveling times of the sound command to each of three microphones has been used to calculate the distance and orientation of the sound from the cleaning mobile robot, which carries the microphone array. The cross-correlation between two signals has been applied for detecting the time difference between two signals, which provides reliable and precise value of the time difference compared to the conventional methods. To generate the tracking direction to the sound command, fuzzy rules are applied and the results are used to control the cleaning mobile robot in a real-time. Finally the experiment results show that the proposed algorithm works well, even though the mobile robot knows little about the environment.

Color Pattern Recognition and Tracking for Multi-Object Tracking in Artificial Intelligence Space (인공지능 공간상의 다중객체 구분을 위한 컬러 패턴 인식과 추적)

  • Tae-Seok Jin
    • Journal of the Korean Society of Industry Convergence
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    • v.27 no.2_2
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    • pp.319-324
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    • 2024
  • In this paper, the Artificial Intelligence Space(AI-Space) for human-robot interface is presented, which can enable human-computer interfacing, networked camera conferencing, industrial monitoring, service and training applications. We present a method for representing, tracking, and objects(human, robot, chair) following by fusing distributed multiple vision systems in AI-Space. The article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguous conditions. We propose to track the moving objects(human, robot, chair) by generating hypotheses not in the image plane but on the top-view reconstruction of the scene.

Engineering Students' Ethical Sensitivity on Artificial Intelligence Robots (공학전공 대학생의 AI 로봇에 대한 윤리적 민감성)

  • Lee, Hyunok;Ko, Yeonjoo
    • Journal of Engineering Education Research
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    • v.25 no.6
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    • pp.23-37
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    • 2022
  • This study evaluated the engineering students' ethical sensitivity to an AI emotion recognition robot scenario and explored its characteristics. For data collection, 54 students (27 majoring in Convergence Electronic Engineering and 27 majoring in Computer Software) were asked to list five factors regarding the AI robot scenario. For the analysis of ethical sensitivity, it was checked whether the students acknowledged the AI ethical principles in the AI robot scenario, such as safety, controllability, fairness, accountability, and transparency. We also categorized students' levels as either informed or naive based on whether or not they infer specific situations and diverse outcomes and feel a responsibility to take action as engineers. As a result, 40.0% of students' responses contained the AI ethical principles. These include safety 57.1%, controllability 10.7%, fairness 20.5%, accountability 11.6%, and transparency 0.0%. More students demonstrated ethical sensitivity at a naive level (76.8%) rather than at the informed level (23.2%). This study has implications for presenting an ethical sensitivity evaluation tool that can be utilized professionally in educational fields and applying it to engineering students to illustrate specific cases with varying levels of ethical sensitivity.