Dr. Ayanna Howard
Dr. Ayanna Howard is an Associate Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. She received her B.S. from Brown University, her M.S.E.E. from the University of Southern California, and her Ph.D. in Electrical Engineering from the University of Southern California in 1999. Her area of research is centered around the concept of humanized intelligence, the process of embedding human cognitive capability into the control path of autonomous systems. This work, which addresses issues of autonomous control as well as aspects of interaction with humans and the surrounding environment, has resulted in over 100 peer-reviewed publications on a number of projects – from scientific rover navigation in glacier environments to assistive robots for the home. To date, her unique accomplishments have been highlighted through a number of awards and articles, including highlights in USA Today, Upscale, and TIME Magazine, as well as being named a MIT Technology Review top young innovator of 2003, receiving the Georgia-Tech Faculty Women of Distinction Award in 2008, and recognized as NSBE Educator of the Year in 2009. From 1993-2005, Dr. Howard was at NASA's Jet Propulsion Laboratory, California Institute of Technology. Following this, she joined Georgia Tech in July 2005 and founded the Human-Automation Systems Lab. She also serves as Chair of the multidisciplinary Robotics Ph.D. program at Georgia Tech.
SnoMotes: Robotic Scientific Explorers for Understanding Climate Change
Recently, it has been discovered that the giant ice sheets covering Greenland and Antarctica have been shrinking at an accelerated rate. While it is believed that these regions hold important information related to global climate change, there is still insufficient data to be able to accurately predict the glacial behavior and the subsequent global ramifications. Satellites have been able to map the ice sheet elevations with increasing accuracy, but data about general weather conditions (i.e. wind speed, barometric pressure, etc.) must be measured at the surface. In order to obtain a denser set of measurements, human expeditions could be sent to these remote and dangerous areas. Alternatively, a group of autonomous robotic rovers could be deployed to these same locations, mitigating the cost, effort, and danger of human presence. For this to be a viable solution though, methodologies must be developed for deployment of this surface-based mobile science network in these arctic environments. Specific technological achievements that must be achieved include designing a robust Arctic rover platform, autonomous methods for navigating arctic terrain, and developing human-inspired schemes to deploy multiple robotic scientific explorers to specific science sites of interest. In this talk, we discuss an infrastructure that addresses these issues in order to enable successful deployment of these robotic scientific explorers.