Lockheed Martin Robotics Seminar: Dr. Volkan Isler, "Robots in Farm and Wildlife"
Friday, April 5, 2019
2121 JM Patterson
301 405 4358
Lockheed Martin Robotics Seminar Series
Robots in Farm and Wildlife
Department of Computer Science and Engineering
University of Minnesota, Twin Cities
In this talk, I will give an overview of our efforts on building robotic systems which can collect semantic data for agricultural and environmental monitoring applications. I will present examples of systems we built for mapping yield in apple orchards and tracking radio tagged land animals and fish. A challenging aspect of these applications is the trade-off between spatial scale (orchards can span thousands of acres) and resolution (fruit diameter is only a few inches). Our approach for tackling these challenges involve developing heterogeneous multi-robot systems which can operate at multiple scales and designing optimal or near-optimal algorithms for solving the associated view planning problems. At the end of the talk, I will give results from our recent efforts to go beyond data collection toward actively changing the environment in applications such as fruit picking and pasture mowing.
Volkan Isler is a Professor in the Computer Science and Engineering Department at the University of Minnesota where he is also a resident fellow at the Institute on Environment and 2010-2012 McKnight Land-Grant Professor. He is currently a visiting professor at Samsung AI Research Center in NY.
In 2008, he received the National Science Foundation's Young Investigator Award (CAREER). From 2009 to 2015, he chaired IEEE Society of Robotics and Automation (RAS) 's Technical Committee on Networked Robots. He also served as an Associate Editor for IEEE Transactions on Robotics and IEEE Transactions on Automation Science and Engineering. He is currently an Editor for RAS Conference Editorial Board.
His research interests are primarily in robotics, computer vision, sensor networks and geometric algorithms, and their applications in agriculture and environmental monitoring.