Joe Moore: Robust Post-Stall Perching with a Fixed-Wing UAV

October 15, 2014 @ 12:00 pm – 1:00 pm
B17 Hackerman Hall
Marin Kobilarov


Consider a bird perching on a branch. In the presence of environmental disturbances and complicated fluid flow, the animal exploits post-stall pressure drag to rapidly decelerate and land on a perch with a precision far beyond the capabilities of our best aircraft control systems. In this talk, I will present methods to improve the robustness of the perching maneuver for a fixed-wing UAV (Unmanned Aerial Vehicle), with the goal of perching on powerlines to recharge. By considering three sources of uncertainty – random initial conditions, model inaccuracy, and external disturbances – I will show that I can apply recent advances in SOS (Sum of Squares) programming to build robust perching controllers. Using a 24-inch wingspan glider, I demonstrate these methods in hardware by landing on a wire from a wide range of hand-launched initial conditions and by perching on an experimental powerline outdoors.


Speaker Bio

Joseph Moore is currently a postdoctoral fellow at the Johns Hopkins Applied Physics Lab in the Robotics and Autonomous Systems group. He completed his Ph.D. and S.M. in the Mechanical Engineering Department at the Massachusetts Institute of Technology where he was a Graduate Research Assistant in the Robot Locomotion Group under Professor Russ Tedrake. He also holds a B.S. in both Mechanical and Electrical Engineering from Rensselaer Polytechnic Institute. Before joining the Robot Locomotion Group in 2008, he worked on Active Flow Control at RPI in the Center for Automation Technologies and Systems and on embedded software development for the Puck motor controller at Barrett Technology. His current work focuses on the control of underactuated systems with uncertain dynamics and the application of these methods to high-performance robotic platforms.



Johns Hopkins University

Johns Hopkins University, Whiting School of Engineering

3400 North Charles Street, Baltimore, MD 21218-2608

Laboratory for Computational Sensing + Robotics