5 accepted papers
The performance of over-actuated Unmanned Aerial Vehicles (UAVs) is significantly influenced by aerodynamic effects, as they are subject to different airflow conditions. For those aerodynamic effects that are difficult to model but could occur repeatedly, Iterative Learning Control (ILC) has great p
Overactuated multirotor unmanned aerial vehicles (UAVs) usually consist of multiple tiltable thrust actuators. The controllers are mostly designed by regarding the thrust forces and actuator tilting angles as inputs of outer-loop position and attitude controllers, while formulating an inner-loop con
Fully-actuated multi-rotor aerial platforms are receiving increasing research interests for the capability of six degree-of-freedom (DOF) motions such as hovering at non-horizontal attitude angles. Existing real world hardware and experiments have demonstrated such capability for a limited range of
Multirotor copters with full six Degree of Freedom (DoF) maneuvering are often overactuated. The control allocation of overactuated UAV platforms can have an infinite number of solutions due to their redundancy. The most common allocation framework is based on Force Decomposition (FD), which provide
The overarching goal of this work is to demonstrate the feasibility of using optical coherence tomography (OCT) to guide a robotic system to extract lens fragments from <i>ex vivo</i> pig eyes. A convolutional neural network (CNN) was developed to semantically segment four intraocular structures (le