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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Stephanie Arévalo Arboleda Söhnke Fischedick Chenayo Diao Kay Richter Horst-Michael Gross Alexander Raake Audiovisual Technology Group Technische Universität Ilmenau Germany Neuroinformatics and Cognitive Robotics Group Technische Universität Ilmenau Germany

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Telepresence robots can enhance communication experiences by providing a sense of physical presence, embodiment and may evoke co-presence. In spite of that, telepresence robots have not made it fully to consumer markets. In this paper, we investigate how different levels of controlling a telepresence robot (teleoperation, shared control, and no control) influence presence. To this aim, we conducted a study (N=45) where participants were evenly distributed to one of the robot control conditions. The task involved navigating an unknown room and listening to stories told by a person co-located with the robot. We collected subjective impressions of presence using the temple presence inventory and performed a thematic content analysis on a post-experiment interview. Our results suggest nuances in perceived presence under different levels of robot control after performing a thematic content analysis. Copresence can be experienced during teleoperation and shared control, and teleoperation may evoke negative sentiments if it does not provide enough spatial information during navigation. However, our results did not point to significant differences in spatial or social presence. We consider that these findings encourage further discussions on how presence is perceived in robot-mediated communication.

关键词： Telepresence Content management Navigation Robot control Robot sensing systems Interviews

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Placing by Touching: An Empirical Study on the Importance of Tactile Sensing for Precise Object Placing

Placing by Touching: An Empirical Study on the Importance of...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Luca Lach Niklas Funk Robert Haschke Séverin Lemaignan Helge Joachim Ritter Jan Peters Georgia Chalvatzaki Neuroinformatics Group Technical Faculty Bielefeld University Institut de Robòtica i Informatica Industrial CSIC- UPC Computer Science Department Technical University Darmstadt PAL Robotics Research Department: Systems AI for Robot Learning German Research Center for AI (DFKI) Hessian AI Centre for Cognitive Science

This work deals with a practical everyday problem: stable object placement on flat surfaces starting from unknown initial poses. Common object-placing approaches require either complete scene specifications or extrinsic sensor measurements, e.g., cameras, that occasionally suffer from occlusions. We propose a novel approach for stable object placing that combines tactile feedback and proprioceptive sensing. We devise a neural architecture called PlaceNet that estimates a rotation matrix, resulting in a corrective gripper movement that aligns the object with the placing surface for the subsequent object manipulation. We compare models with different sensing modalities, such as force-torque, an external motion capture system, and two classical baseline models in real-world object placing tasks with different objects. The experimental evaluation of our placing policies with a set of unseen everyday objects reveals significant generalization of our proposed pipeline, suggesting that tactile sensing plays a vital role in the intrinsic understanding of robotic dexterous object manipulation. Code, models, and supplementary videos are available on https://***/view/placing-by-touching.

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Placing by Touching: An empirical study on the importance of tactile sensing for precise object placing

arXiv

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arXiv 2022年

作者： Lach, Luca Funk, Niklas Haschke, Robert Lemaignan, Séverin Ritter, Helge Joachim Peters, Jan Chalvatzaki, Georgia Neuroinformatics Group Technical Faculty Bielefeld University Germany Institut de Robòtica i Informàtica Industrial CSIC-UPC Spain Computer Science Department Technical University Darmstadt Germany PAL Robotics Research Department: Systems AI for Robot Learning Germany Hessian.AI Centre for Cognitive Science

This work deals with a practical everyday problem: stable object placement on flat surfaces starting from unknown initial poses. Common object-placing approaches require either complete scene specifications or extrinsic sensor measurements, e.g., cameras, that occasionally suffer from occlusions. We propose a novel approach for stable object placing that combines tactile feedback and proprioceptive sensing. We devise a neural architecture that estimates a rotation matrix, resulting in a corrective gripper movement that aligns the object with the placing surface for the subsequent object manipulation. We compare models with different sensing modalities, such as force-torque and an external motion capture system, in real-world object placing tasks with different objects. The experimental evaluation of our placing policies with a set of unseen everyday objects reveals significant generalization of our proposed pipeline, suggesting that tactile sensing plays a vital role in the intrinsic understanding of robotic dexterous object manipulation. Code, models, and supplementary videos are available on https://***/ view/placing-by-touching. Copyright © 2022, The Authors. All rights reserved.

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Tactile-Based Object Pose Estimation Employing Extended Kalman Filter

Tactile-Based Object Pose Estimation Employing Extended Kalm...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Qiguang Lin Chaojie Yan Qiang Li Yonggen Ling Yu Zheng Wangwei Lee Zhaoliang Wan Bidan Huang Xiaofeng Liu Jiangsu Key laboratory of Special Robotic Technology College of IoT Engineering Hohai University Changzhou Jiangsu P.R. China State Key Laboratory of Industrial Control and Technology Zhejiang University Institute of Cyber-System and Control Hangzhou P.R. China Neuroinformatics Group Center for Cognitive Interaction Technology (CITEC) Bielefeld University Bielefeld Germany Tencent Robotics X Shenzhen China School of Computer Science and Engineering Sun Yat-sen University Guangzhou P.R.China

In this paper, we present a new approach to estimate the pose of an object being manipulated by a multi-fingered robotic hand. The method utilizes advanced tactile sensors with high spatial resolution to optimize the estimation of the object's pose using an Extended Kalman Filter (EKF) based approach. We defined and derived the state and measurement equations, as well as evaluated the estimation accuracy in grasping tasks. The approach is able to effectively account for the pose transition caused by tactile pushing, and the mapping from the object's pose to the contact position and normal direction as measured by the tactile sensor. The method was evaluated in multiple grasping experiments in simulation scenarios. Results show that the estimation can converge towards the ground truth in a relatively short period of time, with displacement and rotation errors remaining within acceptable levels. This new method has the potential to improve the accuracy and reliability of robotic grasping and manipulation tasks.

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A Feedback Estimation Approach for Therapeutic Facial Training

A Feedback Estimation Approach for Therapeutic Facial Traini...

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International Conference on Automatic Face and Gesture Recognition

作者： Cornelia Dittmar Joachim Denzler Horst-Michael Gross Neuroinformatics and Cognitive Robotics Lab Ilmenau University of Technology Germany Computer Vision Group Friedrich Schiller University Jena Germany

Neuromuscular retraining is an important part of facial paralysis rehabilitation. To date, few publications have addressed the development of automated systems that support facial training. Current approaches require external devices attached to the patient's face, lack quantitative feedback, and are constrained to one or two facial training exercises. We propose an automated camera-based training system that provides global and local feedback for 12 different facial training exercises. Based on extracted 3D facial features, the patient's performance is evaluated and quantitative feedback is derived. The description of the feedback estimation is supplemented by a detailed experimental evaluation of the 3D feature extraction.

关键词： Feature extraction Training Three-dimensional displays Estimation Face Facial features Medical treatment

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Robotic Companions for Older People: A Case Study in the Wild

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Studies in Health Technology and Informatics 2015年 219卷 147-152页

作者： Doering, Nicola Richter, Katja Gross, Horst-Michael Schroeter, Christof Mueller, Steffen Volkhardt, Michael Scheidig, Andrea Debes, Klaus TU Ilmenau Media Psychology and Media Design Group Germany TU Ilmenau Neuroinformatics and Cognitive Robotics Lab Germany

ISBN: (纸本)9781614995944

Older people tend to have difficulties using unknown technical devices and are less willing to accept technical shortcomings. Therefore, a robot that is supposed to support older people in managing daily life has to adapt to the users' needs and capabilities that are very heterogeneous within the target group. The aim of the presented case study was to provide in-depth insights on individual usage patterns and acceptance of a mobile service robot in real live environments (i.e. in the users' homes). Results from three cases (users aged 67, 78 and 85 living in their own apartments) are reported. Findings on usability and user experience illustrate that the robot has considerable potential to be accepted to support daily living at home. © 2015 The authors and IOS Press. All rights reserved.

关键词： Robots

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Robot companion for domestic health assistance: Implementation, test and case study under everyday conditions in private apartments

Robot companion for domestic health assistance: Implementati...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： H. M. Gross S. Mueller C. Schroeter M. Volkhardt A. Scheidig K. Debes K. Richter N. Doering Neuroinformatics and Cognitive Robotics Lab Ilmenau University of Technology Ilmenau Germany Media Psychology and Media Design Group Ilmenau University of Technology Germany

This paper presents the implementation and evaluation results of the German research project SERROGA (2012 till mid 2015), which aimed at developing a robot companion for domestic health assistance for older people that helps keeping them physically and mentally fit to remain living independently in their own homes for as long as possible. The paper gives an overview of the developed companion robot, its system architecture, and essential skills, behaviors, and services required for a robotic health assistant. Moreover, it presents a new approach allowing a quantitative description and assessment of the navigation complexity of apartments to make them objectively comparable for function tests under real-life conditions. Based on this approach, the results of function tests executed in 12 apartments of project staff and seniors are described. Furthermore, the paper presents findings of a case study conducted with nine seniors (aged 68-92) in their own homes, investigating both instrumental and social-emotional functions of a robotic health assistant. The robot accompanied the seniors in their homes for up to three days assisting with tasks of their daily schedule and health care, without any supervising person being present on-site. Results revealed that the seniors appreciated the robot's health-related instrumental functions and even built emotional bonds with it.

关键词： Robot sensing systems Navigation Robot kinematics Medical services Monitoring Systems architecture

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Facial landmark localization and feature extraction for therapeutic face exercise classification

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 458卷 179-194页

作者： Lanz, Cornelia Olgay, Birant Sibel Denzler, Joachim Gross, Horst-Michael Neuroinformatics and Cognitive Robotics Lab Ilmenau University of Technology Ilmenau Germany Computer Vision Group Friedrich Schiller University Jena Jena Germany

ISBN: (纸本)9783662449103

In this work, we examine landmark localization and feature extraction approaches for the unexplored topic of therapeutic facial exercise recognition. Our goal is to automatically discriminate nine therapeutic exercises that have been determined in cooperation with speech therapists. We use colour, 2.5D and 3D image data that was recorded using Microsoft’s Kinect. Our features comprise statistical descriptors of the face surface curvature as well as characteristic profiles that are derived from face landmarks. For the nine facial exercises, we yield an average recognition accuracy of about 91% in conjunction with manually labeled landmarks. Additionally, we introduce a combined method for automatic landmark localization and compare the results to landmark positions obtained from Active Appearance Model fitting as well as manual labeling. The combined localization method exhibits increased robustness in comparison to AAMs. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Feature extraction

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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