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2008 IEEE International Conference on robotics and Automation (ICRA 2008), vol.5

作者： Leandro Soriano Marcolino Luiz Chaimowicz Vision and Robotics Laboratory (VeRLab) Computer Science Department Federal University of Minas Gerais Brazil

In this paper, we address navigation and coordination methods that allow swarms of robots to converge and spread along complex 2D shapes in environments containing unknown obstacles. Shapes are modeled using implicit functions and a gradient descent approach is used for controlling the swarm. To overcome local minima, that may appear in these scenarios, we use a coordination mechanism that reallocates some robots as "rescuers" and sends them to help other robots that may be trapped. Simulations and real experiments demonstrate the feasibility of the proposed approach.

关键词： Robot kinematics Navigation Shape control robotics and automation Robot sensing systems Convergence Robot vision systems Motion planning Deformable models USA Councils

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IEEE Transactions on Haptics: Editorial

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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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Combinatorial Fusion Criteria for Robot Mapping

Combinatorial Fusion Criteria for Robot Mapping

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Damian M. Lyons D. Frank Hsu Qiang Ma Liang Wang Computer Vision & Robotics Laboratory Department of Computer & Information Science Fordham University Bronx NY USA

We address the problem of sensor fusion for stereo and ultrasound depth measurements for map building for a robot operating in a cluttered environment. In such a situation it's difficult to make useful and realistic assumptions about the sensor or environment statistics. Combinatorial Fusion Analysis is used to develop an approach to fusion with unknown sensor and environment statistics. A metric is proposed that shows when fusion from a set of fusion alternatives will produce a more accurate estimation of depth than either sonar or stereo alone and when not. The metric consists of two criteria: (a) the performance ratio PR(A,B) between sensors A and B, and (b) the diversity d(A,B) between A and B as captured by the rank-score function fA and fB. Experimental results are reported to illustrate that these two CFA criteria are viable predictors to distinguish between positive cases (the combined system performs better than or equal to the individual systems) and negative cases.

关键词： Sensor fusion Robot sensing systems Robot vision systems Statistics computer vision Stereo vision Sonar Mobile robots Ultrasonic imaging Statistical analysis

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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 biologically inspired approach for the control of the hand

A biologically inspired approach for the control of the hand

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Congress on Evolutionary Computation

作者： Emmanouil Hourdakis Michail Maniadakis Panos Trahanias Computational Vision and Robotics Laboratory Foundation for Research and Technology Hellas Heraklion Greece Department of Computer Science University of Crete Greece Postdoctoral researcher with the Computational Vision and Robotics Laboratory Foundation for Research and Technology Hellas Heraklion Greece Head of the Computational Vision and Robotics Laboratory Foundation for Research and Technology Hellas Heraklion Greece Professor with the Department of Computer Science University of Crete Greece

The control of the hand in primate species is characterized by a high dimensionality, due to the large number of joints in the fingers. In this study we present how its manipulation can be simplified without compromising its usage, through a constraint methodology that is inspired from recent neurobiological findings. We further develop a computational model, consisting of several brain areas related to hand control, using a co-evolutionary architecture. Due to its neurobiological basis the methodology gives rise to a number of emergent properties that have been shown to occur in primate species during reach-to-grasp tasks.

关键词： Biological control systems Brain modeling computer science computer architecture Biological system modeling Computational modeling Neurons Biological neural networks computer vision Robot kinematics

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Evaluation of a Parallel Architecture and Algorithm for Mapping and Localization

Evaluation of a Parallel Architecture and Algorithm for Mapp...

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IEEE International Symposium on Computational Intelligence in robotics and Automation (CIRA)

作者： Damian M. Lyons Giselle R. Isner Robotics and Computer Vision Laboratory of the Computer & Information Science Department Fordham University Bronx NY USA Computer & Information Science Department Fordham University Bronx NY USA

The Beowulf cluster approach to parallel computation offers a potentially cheap and robust source of computational power for high complexity algorithms in robotics. The challenge is to integrate this approach with the mobility and time critical response constraints of many robotic algorithms. The key contributions of this paper are: (1) introduction of a computational architecture for integrating a cluster into the control architecture of one or more robots, (2) a cluster implementation of Thrun et al's Concurrent Localization and Mapping (CML) algorithm, and (3) presentation of results to illustrate the performance of the implemented CML algorithm and validate the architectural approach.

关键词： Parallel architectures computer architecture Clustering algorithms Concurrent computing Robot sensing systems robotics and automation Mobile robots Navigation Space technology Computational intelligence

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Selecting and evaluating combinatorial fusion criteria to improve multitarget tracking

Selecting and evaluating combinatorial fusion criteria to im...

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2006 9th International Conference on Information Fusion, FUSION

作者： Frank Hsu, D. Lyons, Damian M. Ai, Jizhou Computer Vision and Robotics Laboratory Department of Computer and Information Science Fordham University Bronx NY 10458 United States

ISBN: (纸本)1424409535

In many useful video tracking situations, targets move through repeated mutual occlusions. As targets undergo occlusions, the feature subsets and combinations of those features that are effective in identifying the target and improving tracking performance may change. We use Combinatorial Fusion Analysis to select and evaluate criteria by which to identify the combination of features that will produce the most accurate tracking. In particular we show that the combination of a pair of features A and B will improve the accuracy only if (a) A and B have relative high performance, and (b) A and B are diverse. We present experimental results from three diverse video sequences to illustrate the performance of the proposed criteria.

关键词： Target tracking

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Fast Separation of Reflection Components using a Specularity-Invariant Image Representation

Fast Separation of Reflection Components using a Specularity...

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IEEE International Conference on Image Processing

作者： Kuk-jin Yoon Yoojin Choi In So Kweon Department Electrical Engineering and Computer Science KAIST Robotics and Computer Vision Laboratory South Korea Dept. Electrical Engineering and Computer Science Robotics and Computer Vision Lab. Korea

In this paper, we propose a fast method for separating reflection components using a single color image. We first propose a specular-free two-band image that is a specularity-invariant color image representation. Reflection components separation is achieved by comparing local ratios at each pixel and making those ratios equal in an iterative framework. The proposed method is very fast and shows reasonable results for textured indoor/outdoor images.

关键词： Reflection Image representation Layout Color Polarization computer vision Image segmentation Filters Lighting Argon

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Biomimetic Centering for Undulatory Robots

Biomimetic Centering for Undulatory Robots

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

作者： M. Sfakiotakis D.P. Tsakiris A. Vlaikidis Computational Vision and Robotics Laboratory Institute of Computer Science FORTH Heraklion Greece

Substantial work exists in the undulatory robotics literature on the mechanical design, modeling, gait generation and implementation of robotic prototypes. However, there appears to have been relatively limited work on the use of exteroceptive sensors in control schemes leading to more complex reactive undulatory behaviors. This paper considers a biologically-inspired sensor-based centering behavior for undulatory robots, originally developed for nonholonomic mobile robots. Adaptation to the significantly more complex dynamics of undulatory locomotors highlights a number of issues related to the use of sensors (possibly distributed over the elongated body of the mechanism) for the generation of reactive behaviors, to biomimetic neuromuscular control and to formation control of multi-undulatory swarms. These issues are explored via computational tools specifically geared towards undulatory locomotion in robotics and biology

关键词： Biomimetics Robot sensing systems Biosensors Mobile robots Biological system modeling Prototypes Mechanical sensors Neuromuscular Biology computing Computational biology

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Selecting and Evaluating Combinatorial Fusion Criteria to Improve Multitarget Tracking

Selecting and Evaluating Combinatorial Fusion Criteria to Im...

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International Conference on Information Fusion

作者： D. Frank Hsu Damian M. Lyons Jizhou Ai Computer Vision & Robotics Laboratory Department of Computer & Information Science Fordham University Bronx NY USA

ISBN: (纸本)1424409535

In many useful video tracking situations, targets move through repeated mutual occlusions. As targets undergo occlusions, the feature subsets and combinations of those features that are effective in identifying the target and improving tracking performance may change. We use combinatorial fusion analysis to select and evaluate criteria by which to identify the combination of features that will produce the most accurate tracking. In particular we show that the combination of a pair of features A and B will improve the accuracy only if (a) A and B have relative high performance, and (b) A and B are diverse. We present experimental results from three diverse video sequences to illustrate the performance of the proposed criteria

关键词： Target tracking Target recognition Humans Hidden Markov models computer vision Video sequences Layout Performance analysis Diversity reception Shape

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