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Intelligent Environments Laboratory

The University of Texas at Austin
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    • Prof. Zoltan Nagy, PhD
    • June Young Park
    • José Ramón Vázquez-Canteli
    • Megan K. McHugh, MSE
    • Ayşegül Demir Dilsiz
    • Hagen Fritz
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November 23, 2018, Filed Under: Past Projects II

Assembling Reconfigurable Endoluminal Surgical (ARES) System

We were developing a modular robotic system that can be swallowed and will assemble inside the G.I. Tract for therapeutic and diagnostic procedures. ETH Zürich is one of four European universities participating in this project, led by Paolo Dario at Scuola Superiore Sant’Anna.

My research involved the investigation of the self-assembly of the ARES robot inside the stomach. Using a specific magnet configuration on the connection face, assembly success rates of up to 90% are possible.

Publications

Z. Nagy, J. J. Abbott, and B. J. Nelson, The Magnetic Self-Aligning Hermaphroditic Connector: A Scalable Approach for Modular Microrobots, in Proc. IEEE/ASME Int. Conf. Advanced Intelligent Mechatronics, 2007, Zurich, Switzerland
doi: 10.1109/AIM.2007.4412519

Z. Nagy, R. Oung, J. J. Abbott, and B. J. Nelson, Experimental Investigation of Magnetic Self-Assembly for Swallowable Modular Robots, in Proc. IEEE/RJS International Conference on Intelligent Robots and Systems (IROS), 2008, Nice, France
doi: 10.1109/IROS.2008.4650662

Z. Nagy and B. J. Nelson, On the Feasibility of Magnetic Self-Assembly for Swallowable Modular Robots, Workshop on MesoScale Robotics for Medical Interventions at the IEEE Int. Conference on Robotics and Automation (ICRA), 2010, Anchorage, AK, USA

Z. Nagy, K. Harada, M. Fluckiger, E. Susilo, I. K. Kaliakatsos, A. Menciassi, E. Hawkes, J. J. Abbott, P. Dario, and B. J. Nelson, Assembling Reconfigurable Endoluminal Surgical Systems: Opportunities and Challenges, International Journal of Biomechatronics and Biomedical Robotics, Vol. 1, No. 1, pp 3-16, 2009
doi: 10.1504/IJBBR.2009.030054

 

Research Highlight

Occupancy detection using Bluetooth

  Gathering occupancy data is considered as one of the grand challenges in building information modeling. Direct occupancy detection methods, Read more 

About Us

The Intelligent Environments Laboratory (IEL), led by Prof. Zoltán Nagy, is an interdisciplinary research group within the Building Energy & Environments (BEE) and Sustainable Systems (SuS) Programs of the Department of Civil, Architectural and Environmental Engineering (CAEE) in the Cockrell School of Engineering of the University of Texas at Austin.

The aim of our research is to rethink the built environment and define Smart Buildings and Cities as spaces that adapt to their occupants and reduce their energy consumption.

We combine data science with building science and apply machine learning to the building and urban scale

Take a look at our projects !

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air handling unit Annex 79 architecture artificial neural network Bluetooth city learn Community engaged research earthquakes environmental monitoring fault detection and diagnostics HVAC integrated design intelligent energy management Lighting Control machine learning Megan McHugh multi-agent systems Occupancy Occupant Centered Control Reinforcement Learning Review Smart Building smart city teaching Thermal Comfort
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Research

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UT Energy App – Privacy Policy

Fault detection and diagnostics of air handling units using machine learning and expert rule-sets

Reinforcement Learning in the Built Environment

Reinforcement learning for urban energy systems & demand response

Multi-Agent Reinforcement Learning for demand response & building coordination

IEA-EBC Annex 79: Occupant Centric Design and Operation of Buildings

People

  • Prof. Zoltan Nagy, PhD
  • June Young Park
  • José Ramón Vázquez-Canteli
  • Megan K. McHugh, MSE

Tags

air handling unit Annex 79 architecture artificial neural network Bluetooth city learn Community engaged research earthquakes environmental monitoring fault detection and diagnostics HVAC integrated design intelligent energy management Lighting Control machine learning Megan McHugh multi-agent systems Occupancy Occupant Centered Control Reinforcement Learning Review Smart Building smart city teaching Thermal Comfort
ITS

301 E Dean Keeton St
Austin, TX 78712
512-555-5555
nagy@utexas.edu

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