A new NSF grant on robotic vision has been awarded. The project will study fast dynamic robot vision with muscle inspired actuators. Project title: Integrated Computer Vision System Based on Human Eye Motion, CMMI 1662029, PI: Ueda (Georgia Tech), $332,659, 7/1/2017-6/30/2020
A team of Georgia Tech researchers is working with a private company to develop the Soldier Vertical Mobility System (SVMS) – a backpack-type propulsion system allows individuals to hover, travel, and maneuver hundreds of feet above the ground. Dr. Jun Ueda‘s lab has been developing an exoskeleton to help push…
An AOARD (part of AFOSR) grant “Hybrid site sensing and human-multi-robot team collaboration for disaster relief at nuclear power plants” has been awarded. Dr. Ueda (as the US co-PI) will work with Dr. Cho in CE (the US PI) and collaborators in the Hanyang University for the development of remote…
Kevin is the GWW ME school’s nomination for the Outstanding Undergraduate Researcher Award. He has been involved in the NSF NRI project on adaptive haptic interface. The award will be given at the Spring Undergraduate Research Symposium on April 18, 2017 in the Student Center Ballroom. Congratulations, Kevin!!
Jun Ueda, Joshua Schultz, and Harry Asada, Cellular Actuators: Modularity and Variability in Muscle-Inspired Actuation, Elsevier, January 2017 [LINK Elsevier.com ] [Google Books Preview]
Efrain Teran and Jun Ueda, Influence of rolling resistance on manual wheelchair dynamics and mechanical efficiency, International Journal of Intelligent Robotics and Applications (IJIRA), Published Online [LINK Springer Nature]. [Abstract] The anatomical model propulsion system (AMPS) was designed to propel manual wheelchairs in a highly repeatable manner while emulating human…
Michael continues his research at the Sandia National Laboratories.
Congratulations, Dr. Kim!! Thesis title: Dynamics-Based Motion De-blurring and Panoramic Image Generation for A Compliant Camera Orientation Mechanism. The work has been supported in part by NSF grants.
Jun Ueda and Yuichi Kurita (ed.), Human Modeling for Bio-Inspired Robotics, ISBN 9780128031377, Academic Press, Elsevier, September 2016