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IEEE Transactions on Haptics: Editorial

IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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The Third International Conference on human-robot interaction

The Third International Conference on human-robot interactio...

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作者： Fong, Terry Dautenhahn, Kerstin Scheutz, Matthias Demiris, Yiannis Intelligent Robotics Group NASA Ames Research Center Department of Artificial Intelligence School of Computer Science University of Herfordshire Herfordshire United Kingdom Adaptive Systems Research Group University of Herfordshire Herfordshire United Kingdom Department of Cognitive Science Computer Science and Informatics Cognitive Science Program Indiana University Bloomington IN United States Intelligent Robotics Team Department of Electrical Engineering Imperial College London London United Kingdom

The third international conference on Human-Robot Interaction (HRI-2008) was held in Amsterdam, The Netherlands, March 12-15, 2008. The theme of HRI-2008, "living with robots," highlights the importance of the technical and social issues underlying human-robot interaction with companion and assistive robots for long-term use in everyday life and work activities. More than 250 researchers, practitioners, and exhibitors attended the conference, and many more contributed to the conference as authors or reviewers. HRI-2009 will be held in San Diego, California, from March 11-13, 2009. Copyright © 2008, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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Camera handoff with adaptive resource management for multi-camera multi-target surveillance

Camera handoff with adaptive resource management for multi-c...

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IEEE 5th International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008

作者： Chen, Chung-Hao Yi, Yao Page, David Abidi, Besma Koschan, Andreas Abidi, Mongi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN 37996 United States GE Global Research Center Niskayuna NY 12309 United States

ISBN: (纸本)9780769533414

Camera handoff is a crucial step to generate a continuously tracked and consistently labeled trajectory of the object of interest in multi-camera surveillance systems. Most existing camera handoff algorithms concentrate on data association, namely consistent labeling, where images of the same object are matched across different cameras. However, most real-time object tracking systems see a decrease in the system's frame rate as the number of tracked objects increases. To address this issue, we propose to incorporate an adaptive resource management mechanism into camera handoff. In so doing, cameras' resources can be dynamically allocated to multiple objects according to their priorities and hence the required minimum frame rate can be maintained. Experimental results illustrate that the proposed camera handoff algorithm is capable of maintaining a constant frame rate and of achieving a substantially improved handoff success rate by approximately 20% in comparison with the algorithm presented by Khan and Shah. © 2008 IEEE.

关键词： Cameras

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Mobile robot localization using panoramic vision and combinations of feature region detectors

Mobile robot localization using panoramic vision and combina...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Arnau Ramisa Adriana Tapus Ramon Lopez de Mantaras Ricardo Toledo Artificial Intelligence Research Institute Spain Robotics Research Lab Interaction Lab Department of Computer Science University of Southern California Los Angeles USA UAB Campus Computer Vision Center Spain

This paper presents a vision-based approach for mobile robot localization. The environmental model is topological. The new approach uses a constellation of different types of affine covariant regions to characterize a place. This type of representation permits a reliable and distinctive environment modeling. The performance of the proposed approach is evaluated using a database of panoramic images from different rooms. Additionally, we compare different combinations of complementary feature region detectors to find the one that achieves the best results. Our experimental results show promising results for this new localization method. Additionally, similarly to what happens with single detectors, different combinations exhibit different strengths and weaknesses depending on the situation, suggesting that a context-aware method to combine the different detectors would improve the localization results.

关键词： Mobile robots computer vision Detectors Robot kinematics Robot localization Feature extraction Fingerprint recognition robotics and automation USA Councils Image databases

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Robust speaker localization system for a humanoid robot in noise and reverberation environments

Robust speaker localization system for a humanoid robot in n...

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39th International Symposium on robotics, ISR 2008

作者： Kim, Ui-Hyun Kim, Jinsung Kim, Doik Kim, Hyogon You, Bum-Jae Department of Computer Science and Radio Communications Engineering Korea University Anam-Dong Sungbuk-Gu Seoul 136-701 Korea Republic of Center for Cognitive Robotics Research Korea Institute of Science and Technology 39-1 Hawolgok-Dong Seongbuk-Gu Seoul 136-791 Korea Republic of

Human-robot interaction (HRI) is an important study to allow more natural and effective communication between humans and robots. Recently, research on HRI has been receiving an increasing amount of attention. In this paper, we report on a speaker localization system for a humanoid robot, as part of an auditory-based system of HRI. Our system uses a six-channel microphone array on a humanoid robot's head. To achieve good results in environments of noise and reverberation, we utilize a pre-emphasis filter;a voice activity detection (VAD) algorithm;and generalized cross correlation with phase transform weighting (GCCPHAT) method. Experimental results show that our speaker localization system for a humanoid robot can successfully localize a speaker's position over the entire azimuth and altitude in noise and reverberation environments.

关键词： Reverberation

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Speaker localization using the TDOA-based feature matrix for a humanoid robot

Speaker localization using the TDOA-based feature matrix for...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Ui-Hyun Kim Jinsung Kim Doik Kim Hyogon Kim Bum-Jae You Department of Computer and Radio Communications Engineering Korea University Seoul South Korea Center of Cognitive Robotics Research Korea Institute of Science and Technology Seoul South Korea

research on human-robot interaction has recently been getting increasing attention. In the research field of human-robot interaction, speech signal processing in particular is the source of much interest. In this paper, we report on a speaker localization system with six microphones for a humanoid robot called MAHRU of KIST and propose a time delay of arrival (TDOA)-based feature matrix with its algorithm based on the minimum sum of absolute errors (MSAE) for sound source localization. The TDOA-based feature matrix is defined as a simple database matrix calculated from pairs of microphones installed on a humanoid robot. To verify the solid performance of our speaker localization system for a humanoid robot, we present the various experimental results for the speech sources at all directions within 5 m distance and the height divided into three parts.

关键词： Robots

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Camera Handoff with Adaptive Resource Management for Multi-camera Multi-target Surveillance

Camera Handoff with Adaptive Resource Management for Multi-c...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Chung-Hao Chen Yi Yao David Page Besma Abidi Andreas Koschan Mongi Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA GE Global Research Center Niskayuna NY USA

Camera handoff is a crucial step to generate a continuously tracked and consistently labeled trajectory of the object of interest in multi-camera surveillance systems. Most existing camera handoff algorithms concentrate on data association, namely consistent labeling, where images of the same object are matched across different cameras. However, most real-time object tracking systems see a decrease in the system's frame rate as the number of tracked objects increases. To address this issue, we propose to incorporate an adaptive resource management mechanism into camera handoff. In so doing, cameras¿ resources can be dynamically allocated to multiple objects according to their priorities and hence the required minimum frame rate can be maintained. Experimental results illustrate that the proposed camera handoff algorithm is capable of maintaining a constant frame rate and of achieving a substantially improved handoff success rate by approximately 20% in comparison with the algorithm presented by Khan and Shah.

关键词： Resource management Surveillance Labeling Real time systems Intelligent robots USA Councils Videoconference Robot vision systems Smart cameras Robot kinematics

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Human-Robot Interaction in Handing-Over Tasks

Human-Robot Interaction in Handing-Over Tasks

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17th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2008), vol.1

作者： Markus Huber Markus Rickert Alois Knoll Thomas Brandt Stefan Glasauer Center of Sensorimotor Research Department of Neurology Ludwig-Maximilians Universitat Munchen Germany Robotics and Embedded Systems Laboratory Department of Computer Science Technische Universitat Munchen Germany Department of Neurology Ludwig-Maximilians Universitat Munchen Germany

In many future joint-action scenarios, humans and robots will have to interact physically in order to successfully cooperate. Ideally, seamless human-robot interaction should not require training for the human, but should be intuitively simple. Nonetheless, seamless interaction and cooperation involve some degree of learning and adaptation. Here, we report on a simple case of physical human-robot interaction, a hand-over task. Even such a basic task as manually handing over an object from one agent to another requires that both partners agree upon certain basic prerequisites and boundary conditions. While some of them are negotiated explicitly, e.g. by verbal communication, others are determined indirectly and adaptively in the course of the cooperation. In the present study, we compared human-human hand-over interaction with the same task done by a robot and a human. To evaluate the importance of biological motion, the robot human interaction was tested with two different velocity profiles: a conventional trapezoidal velocity profile in joint coordinates and a minimum-jerk profile of the end-effector. Our results show a significantly shorter reaction time for minimum jerk profiles, which decreased over the first three hand-overs. The results of our comparison provide the background for implementing effective joint-action strategies in humanoid robot systems.

关键词： Robots

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Modeling Overlapping Execution/Observation Brain Pathways

Modeling Overlapping Execution/Observation Brain Pathways

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International Joint Conference on Neural Networks (IJCNN)

作者： Michail Maniadakis Manolis Hourdakis Panos Trahanias Computational Vision and Robotics Laboratory Institute of Computer Science Foundation for Research and Technology Hellas Heraklion Greece Department of Computer Science University of Crete Greece

Recent brain imaging studies on primates revealed that a network of brain areas is activated both during observation and during execution of movements. The present work aims at modeling this group of areas, implementing a distributed computational system. The modeling process follows the agent-based coevolutionary framework that is very effective in terms of designing complex distributed systems addressing successfully the multi-modality of the interacting regions. The implemented model is successfully embedded in a simulated humanoid robot, replicating existing biological findings.

关键词： Brain modeling Biological system modeling computer science Computational modeling computer architecture computer vision Robot vision systems Laboratories Humanoid robots Humans

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A topology-independent similarity measure for high-dimensional feature spaces

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17th International Conference on Artificial Neural Networks, ICANN 2007

作者： Kerdels, Jochen Peters, Gabriele DFKI German Research Center for Artificial Intelligence Robotics Lab. Robert Hooke Str. 5 D-28359 Bremen Germany University of Dortmund Department of Computer Science Computer Graphics Otto-Hahn-Str. 16 D-44221 Dortmund Germany

ISBN: (纸本)9783540746935

In the field of computer vision feature matching in high dimensional feature spaces is a commonly used technique for object recognition. One major problem is to find an adequate similarity measure for the particular feature space, as there is usually only little knowledge about the structure of that space. As a possible solution to this problem this paper presents a method to obtain a similarity measure suitable for the task of feature matching without the need for structural information of the particular feature space. As the described similarity measure is based on the topology of the feature space and the topology is generated by a growing neural gas, no knowledge about the particular structure of the feature space is needed. In addition, the used neural gas quantizes the feature vectors and thus reduces the amount of data which has to be stored and retrieved for the purpose of object recognition. © Springer-Verlag Berlin Heidelberg 2007.

关键词： computer vision

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