LCSR Seminar: Joe Moore “Design and Control of a Delta-Wing Unmanned Aerial-Aquatic Vehicle”

January 31, 2018 @ 12:00 pm – 1:00 pm
Hackerman B17
Ashley Moriarty


Unmanned aerial-aquatic vehicles (UAAVs) have the potential to dramatically improve remote access of underwater environments. In particular, fixed-wing UAAVs offer a promising means of enabling efficient locomotion in both aerial and aquatic domains through the use of a lifting surface. In this talk, I will present our approach for enabling multi-domain mobility with a small fixed-wing UAAV consisting of a single-propeller and a delta-wing planform. To this end, I will describe how our approach, which relies almost entirely on commercial off-the-shelf (COTs) components, uses feedback control and optimal trajectory design to solve the water-exit problem. I will demonstrate, through both simulation and hardware experiments, that our approach is indeed feasible, and that it has the potential to offer a robust, low-cost solution for enabling mobility in and across the air and water domains.



Dr. Joseph Moore is a member of the Senior Professional Staff at the Johns Hopkins University Applied Physics Lab (JHU/APL). In 2014, he received his Ph.D. in Mechanical Engineering from the Massachusetts Institute of Technology, where he was a Graduate Research Assistant in the Robot Locomotion Group and developed control algorithms for robust post-stall perching with a fixed-wing unmanned aerial vehicle (UAV). He also holds a B.S. in both Mechanical and Electrical Engineering from Rensselaer Polytechnic Institute. While at JHU/APL, Dr. Moore has continued to develop control algorithms for enabling agile flight with fixed-wing UAVs. He has also worked on developing algorithms for control and motion planning of mobile manipulators and heterogeneous multi-robot teams. His current work focuses on extreme short-field landings with fixed-wing UAVs, unmanned aerial-aquatic vehicles (UAAVs), and the development of algorithms for nonlinear model predictive control.

Laboratory for Computational Sensing + Robotics