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GRASP Special Seminar: Shaojie Shen, HKUST, “Robust Autonomous Flight in Cluttered Environments”

October 21, 2015 @ 10:00 am - 11:00 am

ABSTRACT

Micro aerial vehicles (MAVs) offer exceptional mobility  and  perceptual  capabilities  over  ground  platforms,  making  them  particularly  suitable  for  search-and-rescue,  disaster response,  and  inspection  missions  in  which  the  vehicle  must be  able  to  navigate  through  complex  three  dimensional  environments.  In  such  missions,  MAVs  must  be  fully  autonomous in  order  to  stabilize  their  fast  dynamics  and  react  to  changes in  environmental  conditions.  This  talk  summarizes  our  recent advances  in  autonomous  MAVs  with  focus  on  state  estimation and trajectory control: (1) a self-calibrating multi-camera visual-inertial  fusion  approach  with  on-the-fly  initialization  for  rapid deployment of MAVs; (2) a dense visual-inertial fusion approach for  robust  tracking  of  very  aggressive  motions;  (3)  a  real-time trajectory generation approach for high-speed autonomous flight through  cluttered  environments;  and  (4)  experimental  testbed and   system   integration   efforts   at   the   HKUST   UAV   group. Extensive  experimental  results will  be  presented  throughout  the talk.

Presenter

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Shaojie Shen received his B.Eng. degree in Electronic Engineering (Honors Research Option) from the Hong Kong University of Science and Technology in 2009. He received his M.S. in Robotics and Ph.D. in Electrical and Systems Engineering in 2011 and 2014, respectively, all from the University of Pennsylvania. He joined the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology in
September 2014 as an Assistant Professor. His research interests are in the areas of robotics and unmanned aerial vehicles, with focus on state estimation, sensor fusion, computer vision, localization and mapping, and autonomous navigation in complex environments.

Details

Date:
October 21, 2015
Time:
10:00 am - 11:00 am
Event Category: