Wednesday, November 18, 2020 - 3:00pm to 3:30pm
Event Calendar Category
LIDS & Stats Tea
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933 8279 8486
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In recent years, autonomous unmanned aerial vehicles (UAVs) that can execute aggressive (i.e., fast and agile) maneuvers have attracted significant attention. We focus on the design of control algorithms for accurate tracking of such maneuvers. This problem is complicated by aerodynamic effects that significantly impact vehicle dynamics at high speeds. In contrast, typical multicopter controllers that operate at low speeds may neglect vehicle aerodynamics all together. We propose a sensor-based approach to account for high-speed aerodynamics. Our controller directly incorporates linear and angular acceleration measurements to correct for unmodeled dynamics. By applying incremental, or sensor-based, control, it only depends on a simple local approximation of the vehicle dynamics model. It does not rely on any modeling, estimation, or learning of vehicle aerodynamics parameters, and is therefore independent of trajectory and vehicle. The controller enables a quadcopter UAV to track complex 3D trajectories, reaching speeds up to 12.9 m/s (46 km/h) and accelerations up to 2.1g, while keeping the root-mean-square tracking error down to 6.6 cm, in a flight volume that is roughly 18 m by 7 m and 3 m tall.
Ezra Tal is a PhD candidate at MIT AeroAstro, where he works on planning and control for fast and highly-maneuverable robots. He is advised by Prof. Sertac Karaman. Before coming to MIT, Ezra obtained BSc and MSc degrees in aerospace engineering from Delft University of Technology in the Netherlands.