• 제목/요약/키워드: Robot-Human Interaction

검색결과 345건 처리시간 0.02초

POMDP 기반 사용자-로봇 인터랙션 행동 모델 (POMDP-based Human-Robot Interaction Behavior Model)

  • 김종철
    • 제어로봇시스템학회논문지
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    • 제20권6호
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    • pp.599-605
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    • 2014
  • This paper presents the interactive behavior modeling method based on POMDP (Partially Observable Markov Decision Process) for HRI (Human-Robot Interaction). HRI seems similar to conversational interaction in point of interaction between human and a robot. The POMDP has been popularly used in conversational interaction system. The POMDP can efficiently handle uncertainty of observable variables in conversational interaction system. In this paper, the input variables of the proposed conversational HRI system in POMDP are the input information of sensors and the log of used service. The output variables of system are the name of robot behaviors. The robot behavior presents the motion occurred from LED, LCD, Motor, sound. The suggested conversational POMDP-based HRI system was applied to an emotional robot KIBOT. In the result of human-KIBOT interaction, this system shows the flexible robot behavior in real world.

인관과 로봇의 다양한 상호작용을 위한 휴대 매개인터페이스 ‘핸디밧’ (A Portable Mediate Interface 'Handybot' for the Rich Human-Robot Interaction)

  • 황정훈;권동수
    • 제어로봇시스템학회논문지
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    • 제13권8호
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    • pp.735-742
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    • 2007
  • The importance of the interaction capability of a robot increases as the application of a robot is extended to a human's daily life. In this paper, a portable mediate interface Handybot is developed with various interaction channels to be used with an intelligent home service robot. The Handybot has a task-oriented channel of an icon language as well as a verbal interface. It also has an emotional interaction channel that recognizes a user's emotional state from facial expression and speech, transmits that state to the robot, and expresses the robot's emotional state to the user. It is expected that the Handybot will reduce spatial problems that may exist in human-robot interactions, propose a new interaction method, and help creating rich and continuous interactions between human users and robots.

이어핀 삽입 자동화 시스템을 위한 템플릿 매칭 기반 홀 판별 방법 (Hole Identification Method Based on Template Matching for Ear Pins Insertion Automation System)

  • 백종환;이재열;정명수;장민우;신동호;서갑호;홍성호
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2020년도 춘계학술발표대회
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    • pp.330-333
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    • 2020
  • 장신구 산업은 인건비의 비중이 높고 노동자의 역량에 따라 제품의 제작 작업 시간 및 품질의 편차가 심하다. 이에 산업계의 수요에 맞추어 실리콘 금형 표면 지름 0.75mm 홀에 이어핀을 삽입하는 공정을 자동화하기 위하여 삽입 자동화 시스템이 개발되고 있다. 본 논문에서는 이어핀 삽입 자동화시스템에서 적용할 수 있는 템플릿 매칭 방법과 관심 영역 레이블링을 통한 홀 판별 방법을 제안한다. 제안한 방법의 안정성을 확보하기 위하여 실험을 통해 최적의 매칭 방법과 이진화 기법을 적용하였으며 이어핀 홀의 좌표를 확보하여 X-Y 정밀 이송 시스템에 적용할 수 있다.

Comprehensive architecture for intelligent adaptive interface in the field of single-human multiple-robot interaction

  • Ilbeygi, Mahdi;Kangavari, Mohammad Reza
    • ETRI Journal
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    • 제40권4호
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    • pp.483-498
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    • 2018
  • Nowadays, with progresses in robotic science, the design and implementation of a mechanism for human-robot interaction with a low workload is inevitable. One notable challenge in this field is the interaction between a single human and a group of robots. Therefore, we propose a new comprehensive framework for single-human multiple-robot remote interaction that can form an efficient intelligent adaptive interaction (IAI). Our interaction system can thoroughly adapt itself to changes in interaction context and user states. Some advantages of our devised IAI framework are lower workload, higher level of situation awareness, and efficient interaction. In this paper, we introduce a new IAI architecture as our comprehensive mechanism. In order to practically examine the architecture, we implemented our proposed IAI to control a group of unmanned aerial vehicles (UAVs) under different scenarios. The results show that our devised IAI framework can effectively reduce human workload and the level of situation awareness, and concurrently foster the mission completion percentage of the UAVs.

어린이를 위한 소셜 로봇의 심리운동 기반 놀이 활동 개발 (Psychomotorik-based Play Activities for Children by In-home Social Robot)

  • 김다영;최지환;김주현;김민규;정재희;서갑호;이원형
    • 로봇학회논문지
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    • 제17권4호
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    • pp.447-454
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    • 2022
  • This paper presents the psychomotorik-based play activities executed by the social robot at home which helps children's social and emotional development. Based on the theory and practice of the psychomotorik therapy, the play activities were implemented in the close collaboration between psychmotorik experts, service designers and robotics engineers. The designed play activities are classified into four categories depending on the main areas of child development. The robotic system that can express verbal and nonverbal behaviors was developed in order to play games with children and but also to make children have continuous interest during the play activities with it. Finally, the psychomotorik-based play service scenario and interactive robot system were validated by the expert group from the domain of child psychotherapy. The evaluation results showed that the play service and the robot system were appropriately developed for children from the experts point of view.

Errors in Human-Robot Interaction Accidents: A Taxonomy and Network Analysis

  • Brian H.W. GUO;Yonger ZUO;Yang Miang Goh;Jae-Yong Lim
    • 국제학술발표논문집
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    • The 10th International Conference on Construction Engineering and Project Management
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    • pp.1088-1095
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    • 2024
  • To enhance the investigation, analysis, and design of safe human-robot interactions (HRI), this study develops a comprehensive taxonomy of safety-related errors in HRI and examines the relationships between errors and the types and levels of HRI. Analyzing 262 HRI accident case reports, the research identifies and categorizes human and robot errors through qualitative analysis. The resulting taxonomy divides human errors into procedure, intrusion, operation, and situation awareness errors, and robot errors into system and safeguarding failures, operational errors, and design flaws. A network of human and robot errors was developed by applying Gephi to represent the human-robot error interactions. The results indicated that "misjudgment of the robot's operational status," "inadvertent activation of the robot," "working within an energized robotic cell without adequate safety measures," and "failure to deenergize/stop the robot" are among those most frequently linked to robot errors. "Inadequate lockout/tagout" and "absence of human detection and protective stop functions" stand out as the most frequent human-robot error interaction.

과학관에서의 대중 시연을 통한 인간크기 이족보행 휴머노이드 로봇의 평가 연구 (Evaluation Study of a Human-sized Bipedal Humanoid Robot Through a Public Demonstration in a Science Museum)

  • 안태범;강이석
    • 제어로봇시스템학회논문지
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    • 제21권9호
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    • pp.849-857
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    • 2015
  • Although human-sized bipedal humanoid robots have been developed as the ideal form of human-friendly robots, studies of humanoid robots from the user perspective and of actual interaction between humanoid robots and the public in daily environments are few. This paper presents a long-term public demonstration that encouraged interaction between a humanoid robot and unspecified individuals. We have collected a significant amount of subjective evaluation data from the public by performing a storytelling demonstration that enhanced people's empathy towards the robot. The evaluation model consists of the robot's human friendliness, which involves its impression on humans, interaction with humans, and imitation of human motions and the robot's human appearance which involves gender, age, height, and body type. This study shows that there is no significant difference in human-friendliness between gender groups (male and female), while there is a significant difference between age groups (children and adults). In human appearance, it appears that there is no significant difference between either gender groups or age groups, except for the case of the robot's height.

효과적인 인간-로봇 상호작용을 위한 딥러닝 기반 로봇 비전 자연어 설명문 생성 및 발화 기술 (Robot Vision to Audio Description Based on Deep Learning for Effective Human-Robot Interaction)

  • 박동건;강경민;배진우;한지형
    • 로봇학회논문지
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    • 제14권1호
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    • pp.22-30
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    • 2019
  • For effective human-robot interaction, robots need to understand the current situation context well, but also the robots need to transfer its understanding to the human participant in efficient way. The most convenient way to deliver robot's understanding to the human participant is that the robot expresses its understanding using voice and natural language. Recently, the artificial intelligence for video understanding and natural language process has been developed very rapidly especially based on deep learning. Thus, this paper proposes robot vision to audio description method using deep learning. The applied deep learning model is a pipeline of two deep learning models for generating natural language sentence from robot vision and generating voice from the generated natural language sentence. Also, we conduct the real robot experiment to show the effectiveness of our method in human-robot interaction.