• ETRI Journal
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• 제38권6호
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• pp.1229-1239
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• 2016

For efficient interaction between humans and robots, robots should be able to understand the meaning and intention of human behaviors as well as recognize them. This paper proposes an interactive human intention reading method in which a robot develops its own knowledge about the human intention for an object. A robot needs to understand different human behavior structures for different objects. To this end, this paper proposes a hierarchical behavior knowledge network that consists of behavior nodes and directional edges between them. In addition, a human intention reading algorithm that incorporates reinforcement learning is proposed to interactively learn the hierarchical behavior knowledge networks based on context information and human feedback through human behaviors. The effectiveness of the proposed method is demonstrated through play-based experiments between a human and a virtual teddy bear robot with two virtual objects. Experiments with multiple participants are also conducted.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2143-2147
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• 2005

Human-Robot interaction (HRI) has recently become one of the most important issues in the field of robotics. Understanding and predicting the intentions of human users is a major difficulty for robotic programs. In this paper we suggest an interaction method allows the robot to execute the human user's desires in an intelligent room-based domain, even when the user does not give a specific command for the action. To achieve this, we constructed a full system architecture of an intelligent room so that the following were present and sequentially interconnected: decision-making based on the Bayesian belief network, responding to human commands, and generating queries to remove ambiguities. The robot obtained all the necessary information from analyzing the user's condition and the environmental state of the room. This information is then used to evaluate the probabilities of the results coming from the output nodes of the Bayesian belief network, which is composed of the nodes that includes several states, and the causal relationships between them. Our study shows that the suggested system and proposed method would improve a robot's ability to understand human commands, intuit human desires, and predict human intentions resulting in a comfortable intelligent room for the human user.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.120.1-120
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• 2001

This paper proposes a prototype of a safe and reliable wheelchair robot with Human Robot Interaction (HRI). Since the wheelchair users are usually the handicapped, the wheelchair robot must guarantee the safety and reliability for the motion while considering users intention, A single color CCD camera is mounted for input user´s command based on human-friendly gestures, and a ultra sonic sensor array is used for sensing external motion environment. We use face and hand directional gestures as the user´s command. By combining the user´s command with the sensed environment configuration, the planner of the wheelchair robot selects an optimal motion. We implement a prototype wheelchair robot, MR, HURI (Mobile Robot with Human Robot Interaction) ...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.49.1-49
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• 2002

$\textbullet$ Intelligent Space 1. Optimal Camera Arrangement 2. People Tracking 3. Physical Robot 4. Robot Control 5. People Following Robot $\textbullet$ Initial stage for making high-level human robot interaction. http://dfs.iis.u-tokyo.ac.jp/∼leejooho/ispace/.

• International journal of advanced smart convergence
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• 제4권2호
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• pp.154-162
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• 2015

This paper focuses on how cognitive and emotional structures affect humans during long-term interaction. We design an interaction with a turn-based game, the Chopstick Game, in which two agents play with numbers using their fingers. While a human and a robot agent alternate turn, the human user applies herself to play the game and to learn new winning skills from the robot agent. Conventional valence and arousal space is applied to design emotional interaction. For the robotic system, we implement finger gesture recognition and emotional behaviors that are designed for three-dimensional virtual robot. In the experimental tests, the properness of the proposed schemes is verified and the effect of the emotional interaction is discussed.

• 디자인학연구
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• 제19권4호
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• pp.81-90
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• 2006

로봇디자인은 로봇이라는 첨단기술의 결정체와 인간을 연결하는 인터페이스 역할을 한다. 실용화 로봇기술의 성숙기에 접어들고 있는 현재 로봇에 대한 커다란 시장이 형성될 시점에서는 더욱 로봇디자인이 중요하게 될 것이다. 로봇이 인간과 같은 환경에서 살아가기 위해서는 인간 친화적인 인터페이스 디자인 기술과 기존의 로봇개념과는 다른 상호작용(interaction)을 고려한 로봇디자인이 개발되어져야 한다. 본 연구는 사례 연구 형식으로 쇼핑서비스지원 로봇을 대상으로 필요기능을 도출하고, HRI 디자인 요소에 대한 설계를 전개했다. 그리고 쇼핑서비스지원 로봇 디자인을 전개하였다. 특히, 제스처(Gesture), 표정(Expression), 사운드(Sound)의 HRI 디자인 요소 구성을 쇼핑서비스 로봇에 적용하여 구체적인 결과를 도출하였다. HRI 디자인에 대한 유효성 검증을 위해서 모션캡처, 애니메이션, 뇌파, 사운드 등이 통합된 인간과 로봇과의 구체적인 인터랙션을 제시하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.2005-2010
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• 2004

As robots become more prevalent in human daily life, situations requiring interaction between humans and robots will occur more frequently. Therefore, human-robot interaction (HRI) is becoming increasingly important. Although robotics researchers have made many technical developments in their field, intuitive and easy ways for most common users to interact with robots are still lacking. This paper introduces a new approach to enhance human-robot interaction using a semantic symbol language and proposes a method to acquire the intentions of robot users. In the proposed approach, each semantic symbol represents knowledge about either the environment or an action that a robot can perform. Users'intentions are expressed by symbolized multimodal information. To interpret a users'command, a probabilistic approach is used, which is appropriate for interpreting a freestyle user expression or insufficient input information. Therefore, a first-order Markov model is constructed as a probabilistic model, and a questionnaire is conducted to obtain state transition probabilities for this Markov model. Finally, we evaluated our model to show how well it interprets users'commands.

• 로봇학회논문지
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• 제5권3호
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• pp.224-230
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• 2010

As robots are no longer just working labors in the industrial fields, but stepping into the human's daily lives, interaction and communication between human and robot is becoming essential. For this social interaction with humans, emotion generation of a robot has become necessary, which is a result of very complicated process. Concept of mood has been considered in psychology society as a factor that effects on emotion generation, which is similar to emotion but not the same. In this paper, mood factors for robot considering not only the conditions of the robot itself but also the circumstances of the robot are listed, chosen and finally considered as elements defining a 2-dimensional mood space. Moreover, architecture that combines the proposed mood model and a emotion generation module is given at the end.

• 제어로봇시스템학회논문지
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• 제14권2호
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• pp.178-183
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• 2008

Human motion analysis is researched as a new method for human-robot interaction (HRI) because it concerns with the key techniques of HRI such as motion tracking and pose recognition. To analysis human motion, extracting features of human body from sequential images plays an important role. After finding the silhouette of human body from the sequential images obtained by CCD color camera, the skeleton model is frequently used in order to represent the human motion. In this paper, using the silhouette of human body, we propose the feature extraction method based on hybrid skeleton for detecting human motion. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• 로봇학회논문지
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• 제1권2호
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• pp.158-162
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• 2006

This paper presents a speaker recognition system intended for use in human-robot interaction. The proposed speaker recognition system can achieve significantly high performance in the Ubiquitous Robot Companion (URC) environment. The URC concept is a scenario in which a robot is connected to a server through a broadband connection allowing functions to be performed on the server side, thereby minimizing the stand-alone function significantly and reducing the robot client cost. Instead of giving a robot (client) on-board cognitive capabilities, the sensing and processing work are outsourced to a central computer (server) connected to the high-speed Internet, with only the moving capability provided by the robot. Our aim is to enhance human-robot interaction by increasing the performance of speaker recognition with multiple microphones on the robot side in adverse distant-talking environments. Our speaker recognizer provides the URC project with a basic interface for human-robot interaction.