• 제목/요약/키워드: human-robot interactive

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A Human Robot Interactive System 'RoJi '

  • Yoon, Joongsun
    • Journal of Mechanical Science and Technology
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    • 제18권11호
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    • pp.1900-1908
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    • 2004
  • A human-friendly interactive system that is based on the harmonious symbiotic coexistence of human and robots is explored. Based on interactive technology paradigm, a robotic cane is proposed for blind or visually impaired travelers to navigate safely and quickly through obstacles and other hazards faced by blind pedestrians. Robotic aids, such as robotic canes, require cooperation between human and robots. Various methods for implementing the appropriate cooperative recognition, planning, and acting, have been investigated. The issues discussed include the interaction between humans and robots, design issues of an interactive robotic cane, and behavior arbitration methodologies for navigation planning.

A Human Robot Interactive System "RoJi"

  • Shim, In-Bo;Yoon, Joong-Sun
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.2670-2675
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    • 2003
  • A human-friendly interactive system, based on the harmonious symbiotic coexistence of human and robots, is explored. Based on interactive technology paradigm, a robotic cane is proposed for blind or visually impaired travelers to navigate safely and quickly among obstacles and other hazards faced by blind pedestrians. Robotic aids, such as robotic canes, require cooperation between humans and robots. Various methods for implementing the appropriate cooperative recognition, planning, and acting, have been investigated. The issues discussed include the interaction of human and robot, design issues of an interactive robotic cane, and behavior arbitration methodologies for navigation planning.

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An Interactive Robotic Cane

  • Yoon, Joongsun
    • International Journal of Precision Engineering and Manufacturing
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    • 제5권1호
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    • pp.5-12
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    • 2004
  • A human-friendly interactive system that is based on the harmonious symbiotic coexistence of human and robots is explored. Based on this interactive technology paradigm, a robotic cane is proposed for blind or visually impaired travelers to navigate safely and quickly through obstacles and other hazards faced by blind pedestrians. The proposed robotic cane, "RoJi,” consists of a long handle with a button-operated interface and a sensor head unit that is attached at the distal end of the handle. A series of sensors, mounted on the sensor head unit, detect obstacles and steer the device around them. The user feels the steering command as a very noticeable physical force through the handle and is able to follow the path of the robotic cane easily and without any conscious effort. The issues discussed include methodologies for human-robot interactions, design issues of an interactive robotic cane, and hardware requirements for efficient human-robot interactions.ions.

표정 피드백을 이용한 딥강화학습 기반 협력로봇 개발 (Deep Reinforcement Learning-Based Cooperative Robot Using Facial Feedback)

  • 전해인;강정훈;강보영
    • 로봇학회논문지
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    • 제17권3호
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    • pp.264-272
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    • 2022
  • Human-robot cooperative tasks are increasingly required in our daily life with the development of robotics and artificial intelligence technology. Interactive reinforcement learning strategies suggest that robots learn task by receiving feedback from an experienced human trainer during a training process. However, most of the previous studies on Interactive reinforcement learning have required an extra feedback input device such as a mouse or keyboard in addition to robot itself, and the scenario where a robot can interactively learn a task with human have been also limited to virtual environment. To solve these limitations, this paper studies training strategies of robot that learn table balancing tasks interactively using deep reinforcement learning with human's facial expression feedback. In the proposed system, the robot learns a cooperative table balancing task using Deep Q-Network (DQN), which is a deep reinforcement learning technique, with human facial emotion expression feedback. As a result of the experiment, the proposed system achieved a high optimal policy convergence rate of up to 83.3% in training and successful assumption rate of up to 91.6% in testing, showing improved performance compared to the model without human facial expression feedback.

유전알고리즘을 이용한 사족 보행로봇의 인간친화동작 구현 (The Implementation of Human-Interactive Motions for a Quadruped Robot Using Genetic Algorithm)

  • 공정식;이인구;이보희
    • 제어로봇시스템학회논문지
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    • 제8권8호
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    • pp.665-672
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    • 2002
  • This paper deals with the human-interactive actions of a quadruped robot by using Genetic Algorithm. In case we have to work out the designed plan under the special environments, our robot will be required to have walking capability, and patterns with legs, which are designed like gaits of insect, dog and human. Our quadruped robot (called SERO) is capable of not only the basic actions operated with sensors and actuators but also the various advanced actions including walking trajectories, which are generated by Genetic Algorithm. In this paper, the body and the controller structures are proposed and kinematics analysis are performed. All of the suggested motions of SERO are generated by PC simulation and implemented in real environment successfully.

Interactive Human Intention Reading by Learning Hierarchical Behavior Knowledge Networks for Human-Robot Interaction

  • Han, Ji-Hyeong;Choi, Seung-Hwan;Kim, Jong-Hwan
    • 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.

감정 경계를 이용한 로봇의 생동감 있는 얼굴 표정 구현 (Life-like Facial Expression of Mascot-Type Robot Based on Emotional Boundaries)

  • 박정우;김우현;이원형;정명진
    • 로봇학회논문지
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    • 제4권4호
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    • pp.281-288
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    • 2009
  • Nowadays, many robots have evolved to imitate human social skills such that sociable interaction with humans is possible. Socially interactive robots require abilities different from that of conventional robots. For instance, human-robot interactions are accompanied by emotion similar to human-human interactions. Robot emotional expression is thus very important for humans. This is particularly true for facial expressions, which play an important role in communication amongst other non-verbal forms. In this paper, we introduce a method of creating lifelike facial expressions in robots using variation of affect values which consist of the robot's emotions based on emotional boundaries. The proposed method was examined by experiments of two facial robot simulators.

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인터액티브 로봇 지팡이 (Hardware Solutions for Interactive Robotic Cane)

  • 심인보;윤중선
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2002년도 춘계학술대회 논문집
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    • pp.338-341
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    • 2002
  • A human-friendly interactive system, based on the harmonious symbiotic coexistence of humans and robots, is explored. Based on this interactive technology paradigm, a robotic cane is designed to help blind or visually impaired travelers to navigate safely and quickly among obstacles and other hazards faced by blind pedestrians. We outline a set of the hardware solutions and working methodologies that can be used for successfully implementing and extending the interactive technology to complex environments, robots, and humans. The issues discussed include the interaction of human and robot, design issue of robotic cane, hardware requirements for efficient human-robot interaction.

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Evolution of a Robotic Cane

  • Yoon, Joong-Sun;Kim, Jin-Young
    • 한국지능시스템학회논문지
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    • 제14권5호
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    • pp.635-641
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    • 2004
  • A human-friendly interactive system that is based on the harmonious symbiotic coexistence of human and robots is explored. Based on interactive technology paradigm, a robotic cane is proposed for blind or visually impaired travelers to navigate safely and quickly through obstacles and other hazards faced by blind pedestrians. Robotic aids, such as robotic canes, require cooperation between human and robots. Various methods for implementing the appropriate cooperative recognition, planning, and acting, have been investigated. The issues discussed include the interaction of human and robot, design issues of an interactive robotic cane, and behavior arbitration methodologies for navigation planning.

Co-Operative Strategy for an Interactive Robot Soccer System by Reinforcement Learning Method

  • Kim, Hyoung-Rock;Hwang, Jung-Hoon;Kwon, Dong-Soo
    • International Journal of Control, Automation, and Systems
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    • 제1권2호
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    • pp.236-242
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    • 2003
  • This paper presents a cooperation strategy between a human operator and autonomous robots for an interactive robot soccer game, The interactive robot soccer game has been developed to allow humans to join into the game dynamically and reinforce entertainment characteristics. In order to make these games more interesting, a cooperation strategy between humans and autonomous robots on a team is very important. Strategies can be pre-programmed or learned by robots themselves with learning or evolving algorithms. Since the robot soccer system is hard to model and its environment changes dynamically, it is very difficult to pre-program cooperation strategies between robot agents. Q-learning - one of the most representative reinforcement learning methods - is shown to be effective for solving problems dynamically without explicit knowledge of the system. Therefore, in our research, a Q-learning based learning method has been utilized. Prior to utilizing Q-teaming, state variables describing the game situation and actions' sets of robots have been defined. After the learning process, the human operator could play the game more easily. To evaluate the usefulness of the proposed strategy, some simulations and games have been carried out.