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Learning Algorithms and Systems Laboratory (LASA)
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Last Update 2007/4/1 19:58
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Category
Laboratory
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Description
LASA Laboratory EPFL, Ecole Polytechnique Federale de Lausanne
Fields covered at LASA include: Learning and Dynamical Systems, Neural Computation and Modeling, Human-Machine Interaction, Humanoids Robotics, Mechatronics, Design of Therapeutic and Educational Robotic Systems.
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Ishikawa Namiki Komuro Laboratory
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Last Update 2006/1/14 23:12
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Category
Laboratory
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Description
Ishikawa Namiki Laboratory, Department of Information Physics and Computing, Graduate School of Information Science and Technology, University of Tokyo
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Intelligent Systems Division
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Last Update 2006/1/20 19:41
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Category
Laboratory
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Description
Intelligent Systems Division, Dept. of Precision Engineering, Graduate School of Engineering, The University of Tokyo
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Institute for Safety Security Rescue Technology
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Last Update 2007/4/1 20:29
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Category
Laboratory
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Description
iSSRt is a State of Florida Type II center whose mission is to lead the way in innovating and propagating information and intelligent systems (unmanned systems, computer vision, intelligent networks, sensors and perception, protocols and team processes) for the unique needs of homeland security and defense. iSSRt is unique in its commitment to the entire R&D cycle of basic research, industry transfer through its NSF industry consortium, and field evaluation. Over 14 USF faculty are involved from three USF campuses (Tampa, St. Pete, Lakeland). iSSRt actively partners with other USF centers and universities to promote true multi-disciplinary work.
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Human-Machine Teaming laboratory
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Last Update 2006/7/17 11:15
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Category
Laboratory
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Description
The Human-Machine Teaming laboratory was established in September 2003 by Julie A. Adams. The purpose of the laboratory is to investigate and advance issues in Complex Man-Machine Systems interaction with a primary focus on human-robotic interaction. Research focuses on developing interaction for multiple robotic systems and developing distributed artificially intelligent algorithms to support human-robotic interaction.
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Haptic Exploration Laboratory
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Last Update 2006/7/17 11:18
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Category
Laboratory
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Description
The Haptic Exploration Laboratory works with both robotic haptics and human-machine haptic interfaces. In the area of robotic haptics, we enable robots to explore the world through touch, using specialized robotic fingers and sensors and the appropriate planning and control. We are developing new finger designs and algorithms for autonomous and teleoperated haptic exploration. In the area of human-machine haptic interfaces, haptic interfaces are used to add the sense of touch to virtual and teleoperated environments. By creating physically-based mathematical models of interactions in real environments, we can enhance the realism of virtual environments. In addition, haptic feedback and active augmentation modes can improve the performance of robotic assistants in tele- and cooperative manipulation. These systems are evaluated using control theoretic and experimental approaches. This research has applications in many areas, including computer-assisted and simulated surgery, autonomous exploration of hazardous or remote environments, undersea salvage, enabling technologies, and manufacturing and design. Sponsors of our work include NSF, NIH and the Whitaker Foundation. The lab director is Dr. Allison Okamura.
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Distributed Intelligence Laboratory
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Last Update 2006/7/17 11:17
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Category
Laboratory
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Description
The Distributed Intelligence Laboratory was founded in August of 2002 by Prof. Lynne E. Parker and is engaged in research in cooperative robotics and distributed artificial intelligence. Our research is focused on the computational issues of distributed intelligent systems -- particularly embodied intelligent systems that have a physical instantiation in the world, such as multi-robot teams, sensor networks, or software agents. We characterize distributed intelligent systems as multiple entities that integrate perception, reasoning, and action to perform cooperative tasks under circumstances that are insufficiently known in advance, and dynamically changing during task execution.
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