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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： S. Eskiizmirliler M.A. Maier L. Zollo L. Manfredi G. Teti C. Laschi Sorbonne Universite Campus Pierre et Marie Curie Paris ÃŽle-de-France FR INSERM-U742 Paris France Inserm U742 Paris France Université Pierre et Marie Paris France Campus Bio-Medico University Laboratory of Biomedical Robotics & EMC Roma Italy IMT Alti Studi Lucca PhD School in Biorobotics Science and Engineering Lucca Italy ARTS Lab-Advanced Robotics Technology and Systems Laboratory Scuola Superiore Sant'' Anna Pontedera Italy Scuola Superiore Sant'Anna (SSSA) ARTS Lab – Advanced Robotics Technology and Systems Laboratory Pontedera Italy

In this article, we present a neurobiologically inspired multinetwork architecture based on knowledge of cortico-cortical connectivity and its application on an anthropomorphic head-arm-hand robotic system to provide reach-and-grasp kinematics based on multimodal sensorimotor learning. The system incorporates artificial neural network modules (matching units) trained by the locally weighted projection regression (LWPR) algorithm that enables progressive learning from simple to more complex sensorimotor tasks. We report the actual performance of the system by comparing the simulation with the experimental results obtained by the implementation on the real world artefact

关键词： Anthropomorphism Robot sensing systems

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Development of a Bioinstrumentation System in the Interaction between a Human and a Robot

Development of a Bioinstrumentation System in the Interactio...

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2006 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Kazuko Itoh Hiroyasu Miwa Yuko Nukariya Massimiliano Zecca Hideaki Takanobu Stefano Roccella Maria Chiara Carrozza Paolo Dario Atsuo Takanishi ROBOCASA Tokyo Japan Department of Mechanical Engineering Waseda University Tokyo Japan Humanoid Robotics Institute (HRI) Waseda University Tokyo Japan Digital Human Research Center National Institute of Advanced Industrial Science and Technology (AIST) Tokyo Japan Graduate School of Science and Engineering Waseda University Tokyo Japan Department of Mechanical Systems Engineering Kogakuin University Tokyo Japan ASMeW Waseda University Tokyo Japan Scuola Superiore Sant Anna ARTS Laboratory Italy Scuola Superiore Sant' Anna ARTS Lab Pontedera Italy Advanced Research Institute for Science and Engineering Waseda University Tokyo Japan Tokyo Japan

Personal robots, which are expected to become popular in the future, are required to be active in joint work and community life with humans. Such robots must have no bad physical or psychical effect on humans. The psychical effect of a robot on humans has been subjectively measured using questionnaires. However, it has not been objectively measured yet. Human emotion and the consciousness direction can be measured by physiological parameters and body motion, respectively. Therefore, the bioinstrumentation system WB-1 was developed in order to objectively measure the psychical effect of a robot on a human. It can measure physiological parameters such as respiration, heart rate, perspiration and pulse wave, and arm motion. Analyzing human stress in the interaction with a robot from electrocardiogram, the robot could generate a motion for decreasing the stress

关键词： Human robot interaction Robot kinematics Humanoid robots Service robots Psychology Biomedical measurements Biomedical engineering Orbital robotics Intelligent robots Motion measurement

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Fast solvers and Sylvester equations: Both sides now

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COMPUTING IN science & engineering 2005年第6期7卷 74-77页

作者： O'Leary, DP Laboratory of Robotics and Systems in Engineering and Science (LARSyS) Universidade Técnica de Lisboa Lisbon Portugal

In our last homework, we solved large sparse systems of linear equations andlearned that to keep storage and computational costs low, it's very important to exploit structurein our matrix. We exploited sparsity; i... 详细信息

关键词： Equations Matrix decomposition Home computing Sparse matrices Computational efficiency Linear systems Arithmetic Sufficient conditions Eigenvalues and eigenfunctions Gold

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Characterization of bio-synthesized magnetic nanoparticles

Characterization of bio-synthesized magnetic nanoparticles

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Proceedings of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2005

作者： Love, Lonnie J. Yeary, Lucas W. Moon, J.W. Phelps, Tommy J. Rondinone, Adam J. IEEE Robotics and Energetic Systems Group Oak Ridge National Laboratory Environmental Science Division Oak Ridge National Laboratory Chemical Science Division Oak Ridge National Laboratory Engineering Science and Technology Division Oak Ridge National Laboratory

Magnetic nanoparticles have potential utility in a variety of applications ranging from ferrofluids to highly sensitive transduction mechanisms for monitoring and controlling biological activities at the molecular level. This paper describes a novel methodology for bacterial synthesis of a wide range of magnetite-based magnetic nanoparticles. First, this approach is highly scalable and low cost enabling production of large volumes of nanoparticles. Second, like the chemical co-precipitation technique, biologically synthesized materials have the ability to dope magnetite with a wide range of elements enabling fine control over magnetic and thermal properties of the particles. Third, unlike chemical co-precipitation techniques which restrict particle sizes below 20 nm, bacterial synthesis enables control of particle sizes from 10 nm to 100 nm. Finally, we show that some forms of the bio-synthesized materials have a significantly higher saturation magnetization than typical chemically synthesized materials. © 2005 IEEE.

关键词： Nanostructured materials

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Autonomous terrain mapping and classification using hidden Markov models

Autonomous terrain mapping and classification using hidden M...

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2005 IEEE International Conference on robotics and Automation

作者： Wolf, Denis F. Sukhatme, Gaurav S. Fox, Dieter Burgard, Wolfram Robotic Embedded Systems Laboratory Department of Computer Science University of Southern California Los Angeles CA United States Robotics and State Estimation Laboratory Department of Computer Science and Engineering University of Washington Seattle WA United States Department of Computer Science University of Freiburg Freiburg Germany

ISBN: (纸本)078038914X

This paper presents a new approach for terrain mapping and classification using mobile robots with 2D laser range finders. Our algorithm generates 3D terrain maps and classifies navigable and non-navigable regions on those maps using Hidden Markov models. The maps generated by our approach can be used for path planning, navigation, local obstacle avoidance, detection of changes in the terrain, and object recognition. We propose a map segmentation algorithm based on Markov Random Fields, which removes small errors in the classification. In order to validate our algorithms, we present experimental results using two robotic platforms. ©2005 IEEE.

关键词： Mobile robots

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Optical flow-based tracking of deformable objects using a non-prior training active feature model 5th

Optical flow-based tracking of deformable objects using a no...

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5th Pacific Rim Conference on Multimedia, PCM 2004

作者： Kim, Sangjin Kang, Jinyoung Shin, Jeongho Lee, Seongwon Paik, Joonki Kang, Sangkyu Abidi, Besma Abidi, Mongi Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-Dong Tongjak-Ku Seoul156-756 Korea Republic of Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering The University of Tennessee KnoxvilleTN37996-2100 United States

ISBN: (纸本)9783540239857

This paper presents a feature point tracking algorithm using optical flow under the non-prior training active feature model (NPT-AFM) framework. The proposed algorithm mainly focuses on analysis of deformable objects, and provides real-time, robust tracking. The proposed object tracking procedure can be divided into two steps: (i) optical flow-based tracking of feature points and (ii) NPT-AFM for robust tracking. In order to handle occlusion problems in object tracking, feature points inside an object are estimated instead of its shape boundary of the conventional active contour model (ACM) or active shape model (ASM), and are updated as an element of the training set for the AFM. The proposed NPT-AFM framework enables the tracking of occluded objects in complicated background. Experimental results show that the proposed NPT-AFM-based algorithm can track deformable objects in real-time. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Optical flows

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Recognizing interaction from a robot's perspective

Recognizing interaction from a robot's perspective

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： T. Salter F. Michaud K. Dautenhahn D. Letourneau S. Caron LABORIUS-Research Laboratory on Mobile Robotics and Intelligent Systems Department of Electrical Engineering and Computer Engineering Université de Sherbrook Sherbrooke QUE Canada Adaptive Systems Research Group School of Computer Science University of Herfordshire Hatfield UK

For meaningful interaction between a robot and a human, an autonomous robot must recognize whether the experienced situation is created by people or by the environment. Using only proprioceptive data from a mobile robotic platform, we discover that it is possible to distinguish sensory data patterns involving interaction. These patterns are obtained whilst navigating varying environments, both human populated and unpopulated. The paper reports the initial set of trials using Roball, a spherical mobile robot. Also described is the experimental methodology currently followed to validate the hypothesis that child interaction can be perceived directly from navigation sensors onboard a robotic platform.

关键词： Robot sensing systems Mobile robots Human robot interaction Navigation Intelligent robots Sensor phenomena and characterization Infrared sensors Educational institutions Plastics Mobile computing

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A novel approach to proactive human-robot cooperation

A novel approach to proactive human-robot cooperation

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： O.C. Schrempf U.D. Hanebeck A.J. Schmid H. Worn Intelligent Sensor-Actuator-Systems Laboratory Institute of Computer Science and Engineering Universität Karlsruhe Karlsruhe Germany Institute for Process Control and Robotics Universität Karlsruhe Karlsruhe Germany

This paper introduces the concept of proactive execution of robot tasks in the context of human-robot cooperation with uncertain knowledge of the human's intentions. We present a system architecture that defines the necessary modules of the robot and their interactions with each other. The two key modules are the intention recognition that determines the human user's intentions and the planner that executes the appropriate tasks based on those intentions. We show how planning conflicts due to the uncertainty of the intention information are resolved by proactive execution of the corresponding task that optimally reduces the system's uncertainly. Finally, we present an algorithm for selecting this task and suggest a benchmark scenario.

关键词： Robot sensing systems Intelligent robots Uncertainty Application software Humanoid robots Human robot interaction Bayesian methods Intelligent sensors Laboratories Computer science

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Task allocation for event-aware spatiotemporal sampling of environmental variables

Task allocation for event-aware spatiotemporal sampling of e...

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2005 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： M.A. Batalin G.S. Sukhatme Yan Yu R. Pon J. Gordon M.H. Rahimi W.J. Kaiser G.J. Pottie D.E. Estrin Center for Robotics and Embedded Systems Robotic Embedded Systems Laboratory Computer Science Department University of Southern California Los Angeles CA USA Department of Computer Science Center for Embedded Networked Sensing University of California Los Angeles CA USA Department of Electrical Engineering Center for Embedded Networked Sensing University of California Los Angeles CA USA

Monitoring of environmental phenomena with embedded networked sensing confronts the challenges of both unpredictable variability in the spatial distribution of phenomena coupled with the demands for a high spatial sampling rate in three dimensions. For example, low distortion mapping of critical solar radiation properties in forest environments may require two-dimensional spatial sampling rates of greater than 10 samples/m/sup 2/ over transects exceeding 1000 m/sup 2/. Clearly, adequate sampling coverage of such transect requires an impractically large number of sensing nodes. A new approach, networked infomechanical system (NIMS), has been introduced to combine autonomous-articulated and static sensor nodes enabling sufficient spatiotemporal sampling density over large transects to meet a general set of environmental mapping demands. This paper describes our work on the critical parts of NIMS, the task allocation module. We present our methodologies and the two basic greedy task allocation policies - based on time of the task arrival (time policy) and distance from the robot to the task (distance policy). We present results from NIMS deployed in a forest reserve and from a lab testbed. The results show that both policies are adequate for the task of spatiotemporal sampling, but also complement each other. Finally, we suggest the future direction of research that would both help us better quantify the performance of our system and create more complex policies.

关键词： Spatiotemporal phenomena Sampling methods Sensor phenomena and characterization Solar radiation Mobile robots Atmospheric measurements Ecosystems Robot sensing systems Embedded system Computer science

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New memory model for humanoid robots - introduction of co-associative memory using mutually coupled chaotic neural networks

New memory model for humanoid robots - introduction of co-as...

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International Joint Conference on Neural Networks (IJCNN)

作者： K. Itoh H. Miwa Y. Nukariya M. Zecca H. Takanobu P. Dario A. Takanishi Department of Mechanical Engineering Waseda University Tokyo Japan Institute for Biomedical Engineering Waseda University Tokyo Japan Graduate School of Science and Engineering Waseda University Tokyo Japan Scuola Superiore Sant'Anna ARTS Laboratory Pontedera Italy Humanoid Robotics Institute Waseda University Tokyo Japan Department of Mechanical Systems Engineering KOGAKUIN University Tokyo Japan

Personal robots, which are expected to become popular in the future, are required to be active in joint work and community life with humans. Therefore, we have been developing new mechanisms and functions for a humanoid robot that has the ability to express emotions and to communicate with humans in a human-like manner. In 2004, we introduced the "Behavior Model" and "Consciousness Model" to the robot mental model so that the robot generated various kinds of behavior and an object of the robot's behavior became clear. We implemented the mental model in the emotion expression humanoid robot WE-4RII (Waseda Eye No.4 Refined II). Also, we have been studying a system of multiple harmonic oscillators (neurons) interacting via chaotic force since 2002. Each harmonic oscillator is driven by chaotic force whose bifurcation parameter is modulated by the position of the harmonic oscillator. In this paper, we propose an associative memory model using mutually coupled chaotic neural networks for generating an optimum behavior to a stimulus. We implemented this model in the emotional expression humanoid robot WE-4RII (Waseda Eye No.4 Refined II).

关键词： Humanoid robots Mutual coupling Chaos Neural networks Chaotic communication Oscillators Humans Cognitive science Neurons Bifurcation

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