Toward an Autonomous Airborne Scientist for Studying Complex Atmospheric Phenomena

Date/Location Information
Seminar Series: 
CCDC Seminar
Quarter: 
2017b Spring
Talk Date: 
06/09/2017 - 3:00pm - 4:00pm
Room: 
Webb 1100
Speaker Information
Speaker Photograph: 
Speaker name: 
Eric Frew
Speaker Title: 
Associate Professor
Speaker Organization: 
U. Colorado
Speaker Department: 
Aerospace Engineering Sciences
Speaker Short Biography: 
Dr. Eric W. Frew is an associate professor in the Department of Aerospace Engineering Sciences and Director of the Research and Engineering Center for Unmanned Vehicles (RECUV) at the University of Colorado Boulder (CU). He received his B.S. in mechanical engineering from Cornell University in 1995 and his M.S and Ph.D. in aeronautics and astronautics from Stanford University in 1996 and 2003, respectively. Dr. Frew has been designing and deploying unmanned aircraft systems for over fifteen years. His research efforts focus on autonomous flight of heterogeneous unmanned aircraft systems; distributed information-gathering by mobile robots; miniature self-deploying systems; and guidance and control of unmanned aircraft in complex atmospheric phenomena. Dr. Frew was co-leader of the team that performed the first-ever sampling of a severe supercell thunderstorm by an unmanned aircraft. He is currently the CU Site Director for the National Science Foundation Industry / University Cooperative Research Center (IUCRC) for Unmanned Aircraft Systems. He received the NSF Faculty Early Career Development (CAREER) Award in 2009 and was selected for the 2010 DARPA Computer Science Study Group.
Talk Abstract: 

Fixed-wing aerial robotic technology has advanced to the point where platforms fly persistent sampling missions far from remote operators. Likewise, complex atmospheric phenomena can be simulated in near real-time with increasing levels of fidelity. Furthermore, cloud computing technology enables distributed computation on large, dynamic data sets. Combining autonomous airborne sensors with environmental models dispersed over multiple communication and computation channels enables the collection of information essential for examining the fundamental behavior of atmospheric phenomena. This paper describes progress toward the development of an autonomous airborne scientist for studying severe local storms. This autonomous scientist combines unmanned aircraft systems, meshed networked communication, cloud computing infrastructure, online and offline numerical weather models, and new onboard sensors. The existing system architecture will be described along with results from recent field deployments validating and assessing various subsystems.