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2017 IEEE International Conference on Robotics and Automation, ICRA 2017

作者： Han, Fei Reardon, Christopher Parker, Lynne E. Zhang, Hao Human-Centered Robotics Lab Department of Computer Science Colorado School of Mines GoldenCO80401 United States US Army Research Laboratory AdelphiMD20783 United States Distributed Intelligence Laboratory Department of Electrical Engineering and Computer Science University of Tennessee TN37996 United States

ISBN: (纸本)9781509046331

Recognition of sequential human activities, such as 'sitting down' and 'standing up', is a common but challenging problem in human-robot interaction, which requires modeling their underlying temporal patterns. Although previous sequence modeling methods, such as Hidden Conditional Random Fields (HCRFs), demonstrated satisfactory recognition accuracy, they do not explicitly model the uncertainty in underlying temporal patterns, which can provide valuable information to characterize sequential activities. To address this problem, we introduce a novel Minimum Uncertainty HCRF (MU, or μHCRF). Different from traditional HCRF-based techniques that only utilize the negative log-likelihood of the categories' conditional probability as the loss function, the proposed μ-HCRF also introduces a regularization term to model the underlying temporal pattern of the latent variables. As another theoretical contribution, we provide a derivation to show that the formulated problem has a closed-form solution, and prove that inference of the proposed μHCRF is tractable. Extensive empirical study is performed to evaluate our approach, using four public benchmark datasets. Experimental results have shown that our μHCRFs outperform previous techniques and achieve state-of-the-art performance on human activity recognition, especially on sequential activities. © 2017 IEEE.

关键词： human robot interaction

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Mathematical models of adaptation in human-robot collaboration

arXiv

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arXiv 2017年

作者： Nikolaidis, Stefanos Forlizzi, Jodi Hsu, David Shah, Julie Srinivasa, Siddhartha Robotics Institute Carnegie Mellon University Human-Computer Interaction Institute Carnegie Mellon University Department of Computer Science National University of Singapore Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology

A robot operating in isolation needs to reason over the uncertainty in its model of the world and adapt its own actions to account for this uncertainty. Similarly, a robot interacting with people needs to reason over its uncertainty over the human internal state, as well as over how this state may change, as humans adapt to the robot. This paper summarizes our own work in this area, which depicts the different ways that probabilistic planning and game-theoretic algorithms can enable such reasoning in robotic systems that collaborate with people. We start with a general formulation of the problem as a two-player game with incomplete information. We then articulate the different assumptions within this general formulation, and we explain how these lead to exciting and diverse robot behaviors in real-time interactions with actual human subjects, in a variety of manufacturing, personal robotics and assistive care settings. Copyright © 2017, The Authors. All rights reserved.

关键词： Game theory

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Emotion and Memory Model for a Robotic Tutor in a Learning Environment 7

Emotion and Memory Model for a Robotic Tutor in a Learning E...

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7th ISCA Workshop on Speech and Language Technology in Education, SLaTE 2017

作者： Ahmad, Muneeb Imtiaz Mubin, Omar Shahid, Suleman Orlando, Joanne MARCS Institute Human-Machine Interaction Group Western Sydney University Australia School of Computing Engineering and Mathematics Western Sydney University Australia Department of Computer Science Lahore University of Management and Sciences Pakistan School of Education Western Sydney University Australia

In this paper, we present an emotion and memory model for a social robot. The model allowed the robot to create a memory account of a child’s emotional events over 4 individual sessions. The robot then adapted its behaviour based on the developed memory. We tested our model through using the NAO robot. The robot was programmed to teach vocabulary to children during the popular game’Snakes and Ladders’. We conducted a between-subject study with 24 children at a primary school to check the validity of our model. We also evaluated the impact of robot’s positive, negative, and neutral emotional feedback of the NAO robot on children vocabulary learning. Three groups of children (8/group) interacted with the robot for four different times during three weeks. Our results showed that the condition where the robot displayed positive emotional responses had a significant effect on the child’s learning performance as compared to the two other conditions: negative feedback and neutral feedback. In addition, our model helped children in improving their vocabulary. © 2017 7th ISCA Workshop on Speech and Language Technology in Education, SLaTE 2017. All rights reserved.

关键词： computer aided instruction

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Personal fabrication

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Communications of the ACM 2017年第10期60卷 48-49页

作者： Mueller, Stephanie Baudisch, Patrick MIT's Electrical Engineering and Computer Science Department United States MIT CSAIL United States Hasso Plattner Institute Potsdam University Germany Human Computer Interaction Lab United States

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ModLight: Designing a modular light signaling tool for human-robot interaction

ModLight: Designing a modular light signaling tool for human...

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2017 IEEE International Conference on Robotics and Automation, ICRA 2017

作者： Cha, Elizabeth Trehon, Tushar Wathieu, Lancelot Wagner, Christian Shukla, Anurag Mataric, Maja J. Interaction Lab in the Department of Computer Science University of Southern California Los AngelesCA90089 United States Department of Electrical Engineering P.E.S. Institute of Technology Bangalore India Department of Mathematics Georgetown University WashingtonDC20057 United States

ISBN: (纸本)9781509046331

Recent work has shown the potential for lights to act as simple, yet expressive signaling mechanisms for use in a variety of human-robot applications. However, the wide range of robot shapes and sizes makes it difficult for researchers to quickly prototype and evaluate different light configurations and signal designs. In this work, we present the design of ModLight, a modular research tool consisting of a set of low cost light blocks that can be easily reconfigured to fit a myriad of robots and applications. ModLight also provides researchers, designers, and students with open-source software tools that enable them to visually design new signals and easily integrate them into existing systems. This work also serves to motivate the need for further research in developing light behaviors for use in human-robot interaction. Towards this goal, we present our design rationale including a brief analysis of the signaling needs of several robots and applications. © 2017 IEEE.

关键词： human robot interaction

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Precise object detection using local feature for robot manipulator

Precise object detection using local feature for robot manip...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Jae Min Cho KyeKyung Kim Department of Computer Software Korea University of Science and Technology Daejeon Korea ETRI Human Machine Interaction Research Group Daejeon Korea

It is difficult to apply object recognition technology to manufacturing industry because the intrinsic characteristics of an object is easily influenced by the surrounding environment such as lighting condition, background complexity and object shape. This paper proposes a precise object detection method for assembling components by more stable feature extraction. To accomplish it, two images are captured by fine-tuning exposure time for the purpose of complementation of features. Adaptive binarization and differential of Gaussian methods are applied to extracting edge information from each image. In the next step, primary features such as contour lines are extracted from the object using the Fast Hough Transform and candidate lines are selected to become geometric conditions of the object. The precise object region is detected by shape analysis using the four vertices computed by the candidate lines. In addition, the internal features of the object are employed to increase the precision of object detection. As a result, the proposed method improved the accuracy of object detection so that it can be useful in the visual servoing using the robot manipulator.

关键词： Feature extraction Object detection Shape Image edge detection Manipulators Lighting

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Anatomy Builder VR: Embodied VR anatomy learning program to promote constructionist learning

Anatomy Builder VR: Embodied VR anatomy learning program to ...

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2017 ACM SIGCHI Conference on human Factors in Computing Systems, CHI EA 2017

作者： Seo, Jinsil Hwaryoung Smith, Brian Michael Cook, Margaret E. Malone, Erica R. Pine, Michelle Leal, Steven Bai, Zhikun Suh, Jinkyo Soft Interaction Lab Department of Visualization Texas A and M University College StationTX77843 United States Department of Veterinary Integrative Biosciences Texas A and M University United States Soft Interaction Lab Department of Computer Science Texas A and M University United States College of Veterinary Medicine Northeast Agricultural University Harbin150030 China 532 Southwest Parkway College StationTX77840 United States

ISBN: (纸本)9781450346566

We present Anatomy Builder VR, a program that examines how a virtual reality (VR) system can support embodied learning in anatomy education. The backbone of the project is to pursue an alternative constructivist pedagogical model for learning canine anatomy. The main focus of the study was to identify and assemble bones in the live-animal orientation, using real thoracic limb bones in a bone box and digital pelvic limb bones in the Anatomy Builder VR. Eleven college students participated in the study. The pilot study showed that participants most enjoyed interacting with anatomical contents within the VR program. Participants spent less time assembling bones in the VR, and instead spent a longer time tuning the orientation of each VR bone in the 3D space. This study showed how a constructivist method could support anatomy education while using virtual reality technology in an active and experiential way. Copyright © 2017 by the Association for Computing Machinery, Inc. (ACM).

关键词： Virtual reality

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The most efficient sequence of study depends on the type of test 39

The most efficient sequence of study depends on the type of ...

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39th Annual Meeting of the Cognitive science Society: Computational Foundations of Cognition, CogSci 2017

作者： Carvalho, Paulo F. Goldstone, Robert L. Human-Computer Interaction Institute Carnegie Mellon University 5000 Forbes Ave PittsburghPA15213 United States Department of Psychological and Brain Sciences Cognitive Science Program Indiana University 1100 E. 10th St. BloomingtonIN47405 United States

ISBN: (纸本)9780991196760

Previous research has shown that the sequence in which concepts are studied changes how well they are learned. In a series of experiments featuring naturalistic concepts (psychology concepts) and naïve learners, we extend previous research by showing that the sequence of study changes the representation the learner creates of the study materials. Interleaved study leads to the creation of relatively interrelated concepts that are represented by contrast to each other and based on discriminating properties. Blocked study, instead, leads to the creation of relatively isolated concepts that are represented in terms of their central and characteristic properties. The relative benefits of these representations depend on whether the test of conceptual knowledge requires contrastive or characteristic information. These results argue for the integrated investigation of the benefits of different sequences of study as depending on the characteristics of the study and testing situation as a whole. © CogSci 2017.

关键词： interleaving interrelated concepts study sequence

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Soft printing with fabric

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XRDS: Crossroads 2016年第3期22卷 50-53页

作者： Peng, Huaishu Hudson, Scott Mankoff, Jennifer McCann, James Information Science Department Cornell University United States Human-Computer Interaction Institute United States The School of Computer Science Carnegie Mellon University United States Human Computer Interaction Institute Carnegie Mellon University United States Carnegie Mellon University United States

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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