• Title/Summary/Keyword: 인간과 로봇의 상호작용

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Techniques of Editing and Reproducing Robot Operation Data for Direct Teaching (직접 교시 작업을 위한 로봇 작업 정보 편집 및 재생산 기법)

  • Kim, Han-Joon;Wang, Young-Jin;Kim, Jin-Oh;Back, Ju-Hoon
    • Journal of the Korean Society for Precision Engineering
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    • v.30 no.1
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    • pp.96-104
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    • 2013
  • Study of human-robot Interaction gets more and more attention to expand the robot application for tasks difficult by robot alone. Developed countries are preparing for a new market by introducing the concept of 'Co-Robot' model of human-robot Interaction. Our research of direct teaching is a way to instruct robot's trajectory by human's handling of its end device. This method is more intuitive than other existing methods. The benefit of this approach includes easy and fast teaching even by non-professional workers. And it can enhance utilization of robots in small and medium-sized enterprises for small quantity batch production. In this study, we developed the algorithms for creating accurate trajectory from repeated inaccurate direct teaching and GUI for the direct teaching. We also propose the basic framework for direct teaching.

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

  • Park, Dongkeon;Kang, Kyeong-Min;Bae, Jin-Woo;Han, Ji-Hyeong
    • The Journal of Korea Robotics Society
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    • v.14 no.1
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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.

A Study on Interaction Design of Companion Robots Based on Emotional State (감정 상태에 따른 컴패니언 로봇의 인터랙션 디자인 : 공감 인터랙션을 중심으로)

  • Oh, Ye-Jeon;Shin, Yoon-Soo;Lee, Jee-Hang;Kim, Jin-Woo
    • Journal of Digital Contents Society
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    • v.18 no.7
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    • pp.1293-1301
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    • 2017
  • Recent changes in social structure, such as nuclear family and personalization, are leading to personal and social problems, which may cause various problems due to negative emotional amplification. The absence of a family member who gives a sense of psychological stability in the past can be considered as a representative cause of the emotional difficulties of modern people. This personal and social problem is solved through the empathic interaction of the companion robot communication with users in daily life. In this study, we developed sophisticated empathic interaction design through prototyping of emotional robots. As a result, it was confirmed that the face interaction greatly affects the emotional interaction of the emotional robot and the interaction of the robot improves the emotional sense of the robot. This study has the theoretical and practical significance in that the emotional robot is made more sophisticated interaction and the guideline of the sympathetic interaction design is presented based on the experimental results.

Performance Evaluation of Human Robot Interaction Components in Real Environments (실 환경에서의 인간로봇상호작용 컴포넌트의 성능평가)

  • Kim, Do-Hyung;Kim, Hye-Jin;Bae, Kyung-Sook;Yun, Woo-Han;Ban, Kyu-Dae;Park, Beom-Chul;Yoon, Ho-Sub
    • The Journal of Korea Robotics Society
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    • v.3 no.3
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    • pp.165-175
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    • 2008
  • For an advanced intelligent service, the need of HRI technology has recently been increasing and the technology has been also improved. However, HRI components have been evaluated under stable and controlled laboratory environments and there are no evaluation results of performance in real environments. Therefore, robot service providers and users have not been getting sufficient information on the level of current HRI technology. In this paper, we provide the evaluation results of the performance of the HRI components on the robot platforms providing actual services in pilot service sites. For the evaluation, we select face detection component, speaker gender classification component and sound localization component as representative HRI components closing to the commercialization. The goal of this paper is to provide valuable information and reference performance on appling the HRI components to real robot environments.

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Implementation of an Embedded System for an Interaction between Robot Arm and Human Arm Based on Force Control (힘 제어 기반의 로봇 팔과 인간 팔의 상호 작용을 위한 임베디드 시스템 설계)

  • Jeon, Hyo-Won;Jung, Seul
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.11
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    • pp.1096-1101
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    • 2009
  • In this paper, an embedded system has been designed for force control application to interact between a robot arm and a human operator. Force induced by the human operator is converted to the desired position information for the robot to follow. For smooth operations, the impedance force control algorithm is utilized to represent interaction between the robot and the human operator by filtering the force. To improve the performance of position control of the robot arm, a velocity term has been obtained and tested by several filters. A PD controller for position control has been implemented on an FPGA as well. Experimental studies are conducted with the ROBOKER to test the functionality of the designed hardware.

Neural Oscillator based Two-link Robot Arm Control (Neural Oscillator 특성을 활용한 2축 링크 로봇 팔 제어)

  • Kwon, J.S.;Yang, W.;Park, G.T.;You, B.J.
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.1813-1814
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    • 2008
  • 본 논문에서는 생물학적 운동 메카니즘을 유사하게 구현하기 위해 신경 진동자를 이용한 로봇 팔 제어 시스템을 제안한다. 인간 및 동물의 주기적인 자율 운동을 관장하는 Central Pattern Generator (CPG)를 수학적으로 모델링한 신경 진동자는 그 중요 특성의 하나인 entrainment 효과를 보여준다. 일반적으로 우리는 이 기능을 이용하여 미지의 외부 환경 변화와 같은 외란에 적절히 상호 작용할 수 있는 운동을 생성해 낼 수 있다. 이러한 결과를 보이기 위해, 각 관절에 가상의 신경 진동자 모델을 결합하였고 외부 환경의 변화나 외란의 감지를 위한 F/T센서를 팔의 말단에 부착하여 시스템을 구현하였다. 신경 진동자 모델을 결합한 2축 링크 로봇 팔 시스템(real time)은 주어진 목적운동을 (원 운동) 수행함과 동시에 미지의 외부 환경의 변화(임의의 벽)를 인지하여 적절한 모션을 생성하는 지를 살펴본다.

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Zero Accident, Connected Autonomous Driving Vehicle (사고제로, 커넥티드 자율이동체)

  • Choi, J.D.;Min, K.W.;Kim, J.H.;Seo, B.S.;Kim, D.H.;Yoo, D.S.;Cho, J.I.
    • Electronics and Telecommunications Trends
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    • v.36 no.1
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    • pp.22-31
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    • 2021
  • In this thesis, we examine the development status of autonomous mobility services using various artificial intelligence algorithms and propose a solution by combining edge and cloud computing to overcome technical difficulties. A fully autonomous vehicle with enhanced safety and ethics can be implemented using the proposed solution. In addition, for the future of 2035, we present a new concept that enables two- and three-dimensional movement via cooperation between ecofriendly, low-noise, and modular fully autonomous vehicles. The zero-error autonomous driving system will safely and conveniently transport people, goods, and services without time and space constraints and contribute to the autonomous mobility services that are free from movement in connection with various mobility.

Exploring on Possibility of Learning with Robots in the Elementary School Curriculum (초등 정규 교육과정에서 교구 로봇 활용 교육의 가능성 탐색)

  • Park, Ju-Hyun;Han, Jeong-Hye;Jo, Mi-Heon;Park, Ill-Woo;Kim, Jin-Oh
    • 한국정보교육학회:학술대회논문집
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    • 2010.08a
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    • pp.15-18
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    • 2010
  • As robots are proved to be effective in enhancing students' creativity and problem-solving abilities and satisfying various needs in special education for the gifted, many students participate in private education and after-school robot classes. However, it is difficult for students in the lower social economy class to use robots for their learning because of the high expense of robots. On this point, as a part of u-Learnng project, this research attempts to provide students in the lower social economy class with the opportunities to use robots for one year. At the end of the year, we will compare the experimental group and the control group in order to examine learning effects of using robots. Until now we have found many cases that show positive effects of the use of robots in students' learning.

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A Design and Implementation of A Robot Client Middleware for Network-based Intelligent Robot based on Service-Oriented (지능형 네트워크 로봇을 위한 서비스 지향적인 로봇 클라이언트 미들웨어 설계와 구현)

  • Kwak, Dong-Gyu;Choi, Jae-Young
    • The KIPS Transactions:PartA
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    • v.19A no.1
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    • pp.1-8
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    • 2012
  • Network-based intelligent robot is connected with network system, provides interactions with humans, and carries out its own roles on ubiquitous computing environments. URC (Ubiquitous Robot Companion) robot has been proposed to develop network-based robot by applying distributed computing techniques. On URC robot, it is possible to save the computing power of robot client by environments, has been proposed to develop robot software using service-oriented architecture on server-client computing environments. The SOMAR client robot consists of two layers - device service layer and robot service layer. The device service controls physical devices, and the robot service abstracts robot's services, which are newly defined and generated by combining many device services. RSEL (Robot Service Executing Language) is defined in this paper to represent relations and connections between device services and robot services. A RESL document, including robot services by combining several device services, is translated to a programming language for robot client system using RSEL translator, then the translated source program is compiled and uploaded to robot client system with RPC (Remote Procedure Call) command. A SOMAR client system is easy to be applied to embedded systems of host/target architecture. Moreover it is possible to produce a light-weight URC client robot by reducing workload of RSEL processing engine.

The Cognition of Non-Ridged Objects Using Linguistic Cognitive System for Human-Robot Interaction (인간로봇 상호작용을 위한 언어적 인지시스템 기반의 비강체 인지)

  • Ahn, Hyun-Sik
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.11
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    • pp.1115-1121
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    • 2009
  • For HRI (Human-Robot Interaction) in daily life, robots need to recognize non-rigid objects such as clothes and blankets. However, the recognition of non-rigid objects is challenging because of the variation of the shapes according to the places and laying manners. In this paper, the cognition of non-rigid object based on a cognitive system is presented. The characteristics of non-rigid objects are analysed in the view of HRI and referred to design a framework for the cognition of them. We adopt a linguistic cognitive system for describing all of the events happened to robots. When an event related to the non-rigid objects is occurred, the cognitive system describes the event into a sentential form and stores it at a sentential memory, and depicts the objects with a spatial model for being used as references. The cognitive system parses each sentence syntactically and semantically, in which the nouns meaning objects are connected to their models. For answering the questions of humans, sentences are retrieved by searching temporal information in the sentential memory and by spatial reasoning in a schematic imagery. Experiments show the feasibility of the cognitive system for cognizing non-rigid objects in HRI.