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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8755卷 310-319页

作者： Sorostinean, Mihaela Ferland, François Dang, Thi-Hai-Ha Tapus, Adriana Computer Vision and Robotics Lab Computer Science and System Engineering Department ENSTA-ParisTech Palaiseau France

ISBN: (纸本)9783319119724

Various studies have shown that human visual attention is generally attracted by motion in the field of view. In order to embody this kind of social behavior in a robot, its gaze should focus on key points in its environment, such as objects or humans moving. In this paper, we have developed a social natural attention system and we explore the perception of people while interacting with a robot in three different situations: one where the robot has a totally random gaze behavior, one where its gaze is fixed on the person in the interaction, and one where its gaze behavior adapts to the motion-based environmental context. We conducted an online survey and an on-site experiment with the Meka robot so as to evaluate people’s perception towards these three types of gaze. Our results show that motion-oriented gaze can help to make the robot more engaging and more natural to people. © 2014 Springer International Publishing Switzerland.

关键词： Robots

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High dielectric material dependence of carbon nanotube field effect transistor considering non-ballistic conduction

High dielectric material dependence of carbon nanotube field...

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作者： Rouf, Nirjhor Tahmidur Deep, Ashfaqul Haq Hassan, Rusafa Binte Khan, Sabbir Ahmed Hasan, Mahmudul Mominuzzaman, Sharif Mohammad Control and Applications Research Centre BRAC University Dhaka1212 Bangladesh Department of Electrical and Electronic Engineering BRAC University Dhaka1212 Bangladesh BRACU Robotics Research Lab School of Engineering and Computer Science BRAC University Dhaka1212 Bangladesh Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology Dhaka1000 Bangladesh

As a result of this reported research, a simulation model to analyse the behaviour of carbon nanotube field effect transistors (CNTFETs) under non-ballistic conditions is explained and the effect of gate dielectric on the performance of CNTFETs has been explored in detail. For the first time, a thorough study of the combined non-ballistic effect on the performance of CNTFETs has been conducted and the output of the device has been analysed. It has been observed that a gate material with a high dielectric constant leads to higher on-state current and higher on and off state current ratio. In addition, the transconductance, total capacitance, charging energy, subthreshold swing (S), drain-induced barrier lowering (DIBL) and gain with respect to the dielectric constant have been observed and analysed. Transconductance and total capacitance increases by a significant amount, while charging energy and S decrease as the dielectric value increases. The DIBL and gain vary slightly as a higher value dielectric material is used as a gate. Furthermore, the results of this study have been plotted against previously reported ballistic outputs to provide a better perception of the deviation from ideal behaviour. At the same time, the outcomes of this analysis have been compared against some reported experimental values. © The Institution of engineering and Technology 2014.

关键词： Ballistics

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Implementation and test of human-operated and human-like adaptive impedance controls on Baxter robot

Implementation and test of human-operated and human-like ada...

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15th Annual Conference on Advances in Autonomous robotics Systems, TAROS 2014

作者： Liang, Peidong Yang, Chenguang Wang, Ning Li, Zhijun Li, Ruifeng Burdet, Etienne Centre for Robotics and Neural Systems School of Computing and Mathematics Plymouth University United Kingdom MOE Key Lab. of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology China State Key Laboratory of Robotics and System Harbin Institute of Technology China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Department of Bioengineering Imperial College of Science Technology and Medicine London United Kingdom

ISBN: (纸本)9783319104003

This paper presents an improved method to teleoperate impedance of a robot based on surface electromyography (EMG) and test it experimentally. Based on a linear mapping between EMG amplitude and stiffness, an incremental stiffness extraction method is developed, which uses instantaneous amplitude identified from EMG in a high frequency band, compensating for non-linear residual error in the linear mapping and preventing muscle fatigue from affecting the control. Experiments on one joint of the Baxter robot are carried out to test the approach in a disturbance attenuation task, and to compare it with automatic human-like impedance adaptation. The experimental results demonstrate that the new human operated impedance method is successful at attenuating disturbance, and results similarly to as automatic disturbance attenuation, thus demonstrating its efficiency. © 2014 Springer International Publishing.

关键词： Stiffness

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Opening remarks

2016 International Conference on Advances in Human Machine I...

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2016 International Conference on Advances in Human Machine Interaction, HMI 2016 2016年

作者： Nagaraja, Ch. Swamy, J. Nagendra Rajendra, J. Khan, M.S. Vishwanath Reddy, D.S. Manjunath, N. Dillmann, Ruediger Tarn, Tzyh Jong Zhao, Qianchuan Ammi, Mehdi Zuberek, Wlodek M. Sandhu, P.S. Patthira Newman, K. De Silva Liyanage, Chandratilak Hassan, Sohair Aly Aly Sun, Kien Wen Rahman, Md. Moshiur Ordoño, E. Evangelista Sharma, R.K. Mishra, Preeti Chandel, B.S. Singla, Ekta Petric, Tadej Zhong, Yu Jiglar, Janson Alemzadeh, Kazem Asokan, T. Tripathi, Animesh Tripathi, Manoj Ram, Swaminath Shrma, M.K. Panday, P.N. Kumar, Devendra Hinchey, Mike Stilman, Boris Suraj, Zbigniew Pal, Sankar K. Sasi, Sreela Rajan, Deepu Marshall, Roger G. Abraham, Ajith Peter S, David Paul, Vargheese Gopakumar, V. Dustdar, Schahram Soto, Sebastián Ventura Rausch, Andreas Angelis, Lefteris Nelson, Andrew L. Botzheim, Janos Bernardino, Heder Soares Zboril, Frantisek Ane, Bernadetta Kwintiana Maeda, Toshiyuki Sakalauskas, Virgilijus Hann, Garenth Lim King Samek, Jan Romero Salguero, José Raúl Varghese, Kuruvilla Kriksciuniene, Dalia Mathew, Jimson Reif, Wolfgang Mauri, Giancarlo Cabrerizo Lorite, Francisco Javier Özcan, Ender Cho, Sung-Bae Paily, Roy P. Rezankova, Hana Tudjarov, Boris Hong, Wei-Chiang De Oliveira, José Valente Flores Romero, Juan Jose Oskouei, Rozita Jamili Cicchetti, Antonio Roy, Chanchal Segura, Sergio Samuel, C. Mallet, Frédéric Mernik, Marjan Punnekkat, Sasikumar Waseemulla, A. Sri Devaraj Urs Educational Trust Bangalore India R. L. Jalappa Institute of Technology Doddaballapur Bangalore India Humanoids and Intelligence Systems Lab Kalsruhe Germany Electrical and Systems Engineering Washington University in St. Louis United States Deputy Director of Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing China Department of Computer Science CNRS/LIMSI Lab AMI Group France Memorial University St. John'sNL Canada RBIT and Bio-Technology India LR University Thailand University of Colorado at Boulder Boulder United States Faculty of Science University of Brunei Brunei University of Kuala Lumpur Malaysia National Chiao Tung University Taiwan EPR Centre Bangladesh Mapua Institute of Technology Philippines ARO CWC Lucknow India Mpec Kanpur India DSC DBS Kanpu India Indian Institute of Technology Ropar India Jozaf Stefan Institute Department of Automation Biocyernetics and Robotics Ljubljana Slovenia Robotics Institute Carnegie Mellon University Pittsburgh United States Faculty of Engineering University of Bristol United Kingdom Department of Engineering Design Indian Institute of Technology Madras India Lucknow Uni Lucknow India CSJM Uni Kanpur India UPPCB Lucknow India PCB Roorkee India Awadh Uni Faijabad India Agra Uni Agra India Lero University of Limerick Ireland University of Colorado Denver United States University of Rzeszow Poland Indian Statistical Institute Kolkata India Gannon University PA United States Nanyang Technical University Singapore Singapore Plymouth State University NH United States MIR Labs United States Cochin University of Science and Technology India State Project Facilitation Unit TEQIP Kerala India Technical University of Vienna Austria University of Cordoba Spain Clausthal University of Technology Germany Aristotle University of Thessaloniki Greece Androtics LLC TucsonAZ United States Tokyo Metropolitan University Japan Federal Unive

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Determining mood via emotions observed in face by induction

Determining mood via emotions observed in face by induction

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Mojgan Hashemian Hadi Moradi Maryam S Mirian Mehdi Tehrani-doost Advanced Robotics and Intelligent Systems Lab University of Tehran Iran School of Electrical and Computer Engineering University of Tehran Iran Department of Psychiatry Tehran University of Medical Science Iran

Determining the mood of a person is an important step in the Human-Robot interaction. In this paper, we propose a human-inspired approach in which the changes in emotions, done using emotion induction, can be used to determine the mood of a person. The emotion induction, which can be done through robot actions or through showing video clips, stimulates changes in the emotions of the person, reducing the observation time needed to estimate mood. Consequently, the changes in the emotions, which are biased by his/her mood can be used by a robot to determine the mood of a person. To do so, we induced happy emotions by showing a comical clip and measured the intensity of each happy and sad emotions, and also the intensity of the neutral state. Then we extracted a feature set, including both time and frequency domain features, which is used to determine the mood of the person. The approach has been implemented and compared to no-emotion-induction approach and shows better results. Based on the classification results, the approach is able to distinguish between good vs. bad moods with the accuracy of 91.5% with 0.1 mean absolute error. But the neutral state was not distinguishable well.

关键词： Mood Robots Accuracy Feature extraction Face Educational institutions Human-robot interaction

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Determining mood using emotional features

Determining mood using emotional features

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International Symposium on Telecommunications, IST

作者： Mojgan Hashemian Amin Nikoukaran Hadi Moradi Maryam S Mirian Mehdi Tehrani-doost Advanced Robotics and Intelligent Systems Lab University of Tehran Iran School of Electrical and Computer Engineering University of Tehran Iran Department of Psychiatry Tehran University of Medical Science Iran

The ability to determine mood is one of fundamental challenges in affective computing. In this paper, we present a novel approach for mood detection via emotional variations. In this approach, the mood is considered as a low magnitude and more stable, i.e. low frequency, emotion that can be detected using emotion detection approaches. A Bayes classification is applied on a feature vector composed of statistical aspects of the intensity of the emotions. The approach has been implemented in which two emotions, i.e. happiness and sadness, and also neutral state, have been targeted to determine the good, bad, and neutral, mood of subjects respectively. A Bayes classification is applied on a feature vector containing statistical aspects of the intensity of the emotions. The obtained Correct Classification Rate (CCR) is 91.1, with 0.09 mean error and variance of 4.9 discriminating good mood vs. neutral.

关键词： Mood Educational institutions Face Videos computers Mice Accuracy

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Real-timefastest path algorithm using bidirectional point-to-point search on a Fuzzy Time-Dependent transportation network

Real-timefastest path algorithm using bidirectional point-to...

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International Conference on Advanced Logistics and Transport (ICALT)

作者： Mohamed Haitam Laarabi Azedine Boulmakoul Aziz Mabrouk Roberto Sacile Emmanuel Garbolino Department of Computer science Bioengineering Robotics and Systems Engineering University of Genoa Italy Computer Sciences Department LIM/IST Lab. Morocco Department of Mathematics and Computer Sciences Faculty Polydisciplinary of Tetouan Morocco Crisis Research Centre - CRC MINES ParisTech Sophia Antipolis France

Nowadays management of information systems within the transport industry for effective and efficient decision making requires the use of latest technological development such real-time monitoring and traffic simulation. This will lead to the development of methods and algorithms, for instance, of fleet management, routing within a specified time windows and risk assessment. In this paper we will focus on proposing a method for finding itineraries that has the fastest travel-time on a time-dependent transportation network. It is modelled as a weighted graph, whose weight are time duration that depends on the time at which the road segment is traversed. This problem can be solved in polynomial time with a Single-Source algorithm, by the definition of some restrictions on the edge weights. However, its application on a graph with several millions nodes and edges is highly memory and time consuming. Alternatively, a bidirectional Point-to-Point path search, using A-star, offers far better performance. The novelty of the proposed approach is based on the modelling of an appropriate degree of dynamics of a real-world network by considering the fuzzy nature of the travel-time using Zadeh's fuzzy concept. In addition, we speed-up search by integrating a pre-computation phase, which consists in network partitioning using network Voronoi diagrams with implicit calculation of the lower-bound travel-time label for each node-to-border, border-to-border and border-to-node. Those labels should never overestimate the travel-time at any moment, to ensure the reliability of the suggested heuristic cost function.

关键词： Roads Heuristic algorithms Real-time systems Measurement Cost function Libraries Electronic mail

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Teachers' views on the use of empathic robotic tutors in the classroom

Teachers' views on the use of empathic robotic tutors in the...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Sofia Serholt Wolmet Barendregt Iolanda Leite Helen Hastie Aidan Jones Ana Paiva Asimina Vasalou Ginevra Castellano Department of Applied Information Technology University of Gothenburg Gothenburg Sweden GAIPS Instituto Superior Tecnico Lisboa Portugal Social Robotics Lab Yale University New Haven CT USA School of Mathematical and Computer Science Heriot-Watt University Edinburgh UK School of Electronic Electrical and Computer Engineering University of Birmingham Birmingham UK London Knowledge Lab Institute of Education London UK

ISBN: (纸本)9781479967667

In this paper, we describe the results of an interview study conducted across several European countries on teachers' views on the use of empathic robotic tutors in the classroom. The main goals of the study were to elicit teachers' thoughts on the integration of the robotic tutors in the daily school practice, understanding the main roles that these robots could play and gather teachers' main concerns about this type of technology. Teachers' concerns were much related to the fairness of access to the technology, robustness of the robot in students' hands and disruption of other classroom activities. They saw a role for the tutor in acting as an engaging tool for all, preferably in groups, and gathering information about students' learning progress without taking over the teachers' responsibility for the actual assessment. The implications of these results are discussed in relation to teacher acceptance of ubiquitous technologies in general and robots in particular.

关键词： Educational institutions Interviews Robot sensing systems Service robots Europe

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ESICM LIVES 2016: part one Milan, Italy. 1-5 October 2016 Abstracts

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INTENSIVE CARE MEDICINE EXPERIMENTAL 2016年第SUPPL 1期4卷 1-1页

作者： [Anonymous] Academic Medical Center University of Amsterdam Amsterdam Netherlands UMCU Utrecht Netherlands Autonomous University of Barcelona Barcelona Spain Hospital São Francisco Xavier Lisbon Portugal CHU Henri Mondor Medical ICU Créteil France Université de Paris Est-Créteil Groupe de Recherche Clinique CARMAS Créteil France Hôpital Tenon APHP Medical and Surgical ICU Paris France Université Paris Diderot Sorbonne Paris Cité UMR 1153 Paris France Interdepartmental Division of Critical Care University of Toronto Toronto Canada University Health Network University of Toronto Critical Care Medicine Toronto Canada University of Milan - Bicocca Health Sciences School of Medicine and Surgery Monza Italy St Michael’s Hospital University of Toronto Anesthesia Toronto Canada CHU d’Angers Medical ICU Angers France Interdepartmental Division of Critical Care University of Toronto Saint Michael’s Hospital and Keenan Research Centre Toronto Canada University of Birmingham Institute for Inflammation and Ageing Birmingham UK University of Sheffield Mathematics and Statistics Help Centre Sheffield UK Heart of England NHS Foundation Trust Intensive Care Medicine Birmingham UK Department of Surgery University Hospitals Birmingham NHS Trust Birmingham UK University Hospitals Birmingham NHS Trust Anaesthesia and Critical Care Medicine Birmingham UK Queen’s University of Belfast Wellcome-Wolfson Institute for Experimental Medicine Belfast UK Royal Victoria Hospital Intensive Care Medicine Belfast UK University of Warwick Warwick Clinical Trials Unit Coventry UK University of Bari ‘Aldo Moro’ Bari Italy Hospital Israelita Albert Einstein São Paulo Brazil Mayo Clinic Jacksonville USA Mahidol University Faculty of Tropical Medicine Bangkok Thailand University Medical Center Utrecht Intensive Care Utrecht Netherlands University Medical Center Utrecht Julius Center for Health Sciences and Primary Care Utrecht Netherlands Academic Medical Center University of Amste

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ARTIFICIAL ENDOCRINE SYSTEM: A NEW PARADIGM OF KNOWLEDGE DISCOVERY

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International Journal of Information Acquisition 2014年第3N04期9卷

作者： SUBHASH CHANDRA PANDEY GORA CHAND NANDI Computer Science and Engineering Department Birla Institute of Technology Mesra Ranchi (Allahabad Campus) Allahabad UP India Artificial Intelligence and Robotics Lab Indian Institute of Information Technology Allahabad UP India

We propose an artificial endocrine system (AES) for extracting the knowledge from database so that effective and reliable decision rules can be constructed. The proposed AES mimics the functionality of biological endocrine system (BES) to some extent. A mathematical model is proposed for expressive representation of endocrine system as well as for homeostasis. Further, different aspects of our proposed "Artificial endocrine system for knowledge discovery" (AESKD) have been compared with state of art classifiers e.g., support vector machine, neural network, radial basis function (RBF) network and K-NN for some bench mark datasets.

关键词： Bio-inspired computation knowledge discovery data mining artificial endocrine system homeostasis

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