• Title/Summary/Keyword: Human robot interaction

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Computational Model of a Mirror Neuron System for Intent Recognition through Imitative Learning of Objective-directed Action (목적성 행동 모방학습을 통한 의도 인식을 위한 거울뉴런 시스템 계산 모델)

  • Ko, Kwang-Eun;Sim, Kwee-Bo
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.6
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    • pp.606-611
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    • 2014
  • The understanding of another's behavior is a fundamental cognitive ability for primates including humans. Recent neuro-physiological studies suggested that there is a direct matching algorithm from visual observation onto an individual's own motor repertories for interpreting cognitive ability. The mirror neurons are known as core regions and are handled as a functionality of intent recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper, we addressed previous works used to model the function and mechanisms of mirror neurons and proposed a computational model of a mirror neuron system which can be used in human-robot interaction environments. The major focus of the computation model is the reproduction of an individual's motor repertory with different embodiments. The model's aim is the design of a continuous process which combines sensory evidence, prior task knowledge and a goal-directed matching of action observation and execution. We also propose a biologically inspired plausible equation model.

AM-FM Decomposition and Estimation of Instantaneous Frequency and Instantaneous Amplitude of Speech Signals for Natural Human-robot Interaction (자연스런 인간-로봇 상호작용을 위한 음성 신호의 AM-FM 성분 분해 및 순간 주파수와 순간 진폭의 추정에 관한 연구)

  • Lee, He-Young
    • Speech Sciences
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    • v.12 no.4
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    • pp.53-70
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    • 2005
  • A Vowel of speech signals are multicomponent signals composed of AM-FM components whose instantaneous frequency and instantaneous amplitude are time-varying. The changes of emotion states cause the variation of the instantaneous frequencies and the instantaneous amplitudes of AM-FM components. Therefore, it is important to estimate exactly the instantaneous frequencies and the instantaneous amplitudes of AM-FM components for the extraction of key information representing emotion states and changes in speech signals. In tills paper, firstly a method decomposing speech signals into AM - FM components is addressed. Secondly, the fundamental frequency of vowel sound is estimated by the simple method based on the spectrogram. The estimate of the fundamental frequency is used for decomposing speech signals into AM-FM components. Thirdly, an estimation method is suggested for separation of the instantaneous frequencies and the instantaneous amplitudes of the decomposed AM - FM components, based on Hilbert transform and the demodulation property of the extended Fourier transform. The estimates of the instantaneous frequencies and the instantaneous amplitudes can be used for modification of the spectral distribution and smooth connection of two words in the speech synthesis systems based on a corpus.

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Speech Emotion Recognition Using Confidence Level for Emotional Interaction Robot (감정 상호작용 로봇을 위한 신뢰도 평가를 이용한 화자독립 감정인식)

  • Kim, Eun-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.6
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    • pp.755-759
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    • 2009
  • The ability to recognize human emotion is one of the hallmarks of human-robot interaction. Especially, speaker-independent emotion recognition is a challenging issue for commercial use of speech emotion recognition systems. In general, speaker-independent systems show a lower accuracy rate compared with speaker-dependent systems, as emotional feature values depend on the speaker and his/her gender. Hence, this paper describes the realization of speaker-independent emotion recognition by rejection using confidence measure to make the emotion recognition system be homogeneous and accurate. From comparison of the proposed methods with conventional method, the improvement and effectiveness of proposed methods were clearly confirmed.

Comparison of EEG Topography Labeling and Annotation Labeling Techniques for EEG-based Emotion Recognition (EEG 기반 감정인식을 위한 주석 레이블링과 EEG Topography 레이블링 기법의 비교 고찰)

  • Ryu, Je-Woo;Hwang, Woo-Hyun;Kim, Deok-Hwan
    • The Journal of Korean Institute of Next Generation Computing
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    • v.15 no.3
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    • pp.16-24
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    • 2019
  • Recently, research on emotion recognition based on EEG has attracted great interest from human-robot interaction field. In this paper, we propose a method of labeling using image-based EEG topography instead of evaluating emotions through self-assessment and annotation labeling methods used in MAHNOB HCI. The proposed method evaluates the emotion by machine learning model that learned EEG signal transformed into topographical image. In the experiments using MAHNOB-HCI database, we compared the performance of training EEG topography labeling models of SVM and kNN. The accuracy of the proposed method was 54.2% in SVM and 57.7% in kNN.

Role-based Morality, Ethical Pluralism, and Morally Capable Robots

  • Zhu, Qin;Williams, Tom;Wen, Ruchen
    • Journal of Contemporary Eastern Asia
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    • v.20 no.1
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    • pp.134-150
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    • 2021
  • Dominant approaches to designing morally capable robots have been mainly based on rule-based ethical frameworks such as deontology and consequentialism. These approaches have encountered both philosophical and computational limitations. They often struggle to accommodate remarkably diverse, unstable, and complex contexts of human-robot interaction. Roboticists and philosophers have recently been exploring underrepresented ethical traditions such as virtuous, role-based, and relational ethical frameworks for designing morally capable robots. This paper employs the lens of ethical pluralism to examine the notion of role-based morality in the global context and discuss how such cross-cultural analysis of role ethics can inform the design of morally competent robots. In doing so, it first provides a concise introduction to ethical pluralism and how it has been employed as a method to interpret issues in computer and information ethics. Second, it reviews specific schools of thought in Western ethics that derive morality from role-based obligations. Third, it presents a more recent effort in Confucianism to reconceptualize Confucian ethics as a role-based ethic. This paper then compares the shared norms and irreducible differences between Western and Eastern approaches to role ethics. Finally, it discusses how such examination of pluralist views of role ethics across cultures can be conducive to the design of morally capable robots sensitive to diverse value systems in the global context.

Posture Optimization for a Humanoid Robot using Particle Swarm Optimization (PSO를 이용한 휴머노이드 로봇의 최적자세 생성)

  • Yun, JaeHum;Chien, Dang Van;Tin, Tran Trung;Kim, Jong-Wook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.4
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    • pp.450-456
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    • 2014
  • Humanoid robot is the most suitable robot platform for effective human and robot interaction. However, the robot's complicated body structure containing more than twenty joint actuators makes it difficult to generate stable and elaborate postures using the conventional inverse kinematic method. This paper proposes an alternative approach to generate difficult postures of touching an object placed in front of the foot by the left or right hand with its torso bent forward in single support phase using the fast computational optimization method, particle swarm optimization. The simulated postures are also applied to a commercial humanoid robot platform, which validates the feasibility of the proposed approach.

Optimal Joint Trajectory Generation for Biped Walking of Humanoid Robot based on Reference ZMP Trajectory (목표 ZMP 궤적 기반 휴머노이드 로봇 이족보행의 최적 관절궤적 생성)

  • Choi, Nak-Yoon;Choi, Young-Lim;Kim, Jong-Wook
    • The Journal of Korea Robotics Society
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    • v.8 no.2
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    • pp.92-103
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    • 2013
  • Humanoid robot is the most intimate robot platform suitable for human interaction and services. Biped walking is its basic locomotion method, which is performed with combination of joint actuator's rotations in the lower extremity. The present work employs humanoid robot simulator and numerical optimization method to generate optimal joint trajectories for biped walking. The simulator is developed with Matlab based on the robot structure constructed with the Denavit-Hartenberg (DH) convention. Particle swarm optimization method minimizes the cost function for biped walking associated with performance index such as altitude trajectory of clearance foot and stability index concerning zero moment point (ZMP) trajectory. In this paper, instead of checking whether ZMP's position is inside the stable region or not, reference ZMP trajectory is approximately configured with feature points by which piece-wise linear trajectory can be drawn, and difference of reference ZMP and actual one at each sampling time is added to the cost function. The optimized joint trajectories realize three phases of stable gait including initial, periodic, and final steps. For validation of the proposed approach, a small-sized humanoid robot named DARwIn-OP is commanded to walk with the optimized joint trajectories, and the walking result is successful.

Hybrid Silhouette Extraction Using Color and Gradient Informations (색상 및 기울기 정보를 이용한 인간 실루엣 추출)

  • Joo, Young-Hoon;So, Jea-Yun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.7
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    • pp.913-918
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    • 2007
  • Human motion analysis is an important research subject in human-robot interaction (HRI). However, before analyzing the human motion, silhouette of human body should be extracted from sequential images obtained by CCD camera. The intelligent robot system requires more robust silhouette extraction method because it has internal vibration and low resolution. In this paper, we discuss the hybrid silhouette extraction method for detecting and tracking the human motion. The proposed method is to combine and optimize the temporal and spatial gradient information. Also, we propose some compensation methods so as not to miss silhouette information due to poor images. Finally, we have shown the effectiveness and feasibility of the proposed method through some experiments.

Study on Facial Expression Factors as Emotional Interaction Design Factors (감성적 인터랙션 디자인 요소로서의 표정 요소에 관한 연구)

  • Heo, Seong-Cheol
    • Science of Emotion and Sensibility
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    • v.17 no.4
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    • pp.61-70
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    • 2014
  • Verbal communication has limits in the interaction between robot and man, and therefore nonverbal communication is required for realizing smoother and more efficient communication and even the emotional expression of the robot. This study derived 7 pieces of nonverbal information based on shopping behavior using the robot designed to support shopping, selected facial expression as the element of the nonverbal information derived, and coded face components through 2D analysis. Also, this study analyzed the significance of the expression of nonverbal information using 3D animation that combines the codes of face components. The analysis showed that the proposed expression method for nonverbal information manifested high level of significance, suggesting the potential of this study as the base line data for the research on nonverbal information. However, the case of 'embarrassment' showed limits in applying the coded face components to shape and requires more systematic studies.

State Machine design to support behavioral response in DTT protocol (불연속 개별시도 훈련에서 행동 반응을 지원하는 상태머신 설계)

  • Yun, Hyuk;Yun, Sang-Seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.147-149
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    • 2022
  • This paper proposes a state machine design methodology in which an interactive robot that mimics discrete trial training (DTT protocol) can support social interaction training for children with autism. The robot applied to social interaction training uses the response to the provided training stimulus as a quantitative indicator by processing the data received from the sensors measuring the behavioral response of the child. In this process, the state machine is used as information that classifies the state of the acquired data and provides the subsequent stimulus for DTT protocol. Through the joint attentional training, it can be used as evidence-based treatment information by quantitatively classifying the data on the number of sustainable and DTT protocol and the child's response, as well as the current reaction status of the child to the observer performing remote monitoring. At the same time, it was confirmed that it is possible to properly respond to misrecognition situations.

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