Justice in a Pandemic: An Overview of Revised Primary Goods and Policy Tradeoffs

HonorsPhilosophyUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/169428/1/yxilin.pd

Automatic Landing of a Rotary-Wing UAV in Rough Seas

Rotary-wing unmanned aerial vehicles (RUAVs) have created extensive interest in the past few decades due to their unique manoeuverability and because of their suitability in a variety of flight missions ranging from traffic inspection to surveillance and reconnaissance. The ability of a RUAV to operate from a ship in the presence of adverse winds and deck motion could greatly extend its applications in both military and civilian roles. This requires the design of a flight control system to achieve safe and reliable automatic landings. Although ground-based landings in various scenarios have been investigated and some satisfactory flight test results are obtained, automatic shipboard recovery is still a dangerous and challenging task. Also, the highly coupled and inherently unstable flight dynamics of the helicopter exacerbate the difficulty in designing a flight control system which would enable the RUAV to attenuate the gust effect. This thesis makes both theoretical and technical contributions to the shipboard recovery problem of the RUAV operating in rough seas. The first main contribution involves a novel automatic landing scheme which reduces time, cost and experimental resources in the design and testing of the RUAV/ship landing system. The novelty of the proposed landing system enables the RUAV to track slow-varying mean deck height instead of instantaneous deck motion to reduce vertical oscillations. This is achieved by estimating the mean deck height through extracting dominant modes from the estimated deck displacement using the recursive Prony Analysis procedure. The second main contribution is the design of a flight control system with gust-attenuation and rapid position tracking capabilities. A feedback-feedforward controller has been devised for height stabilization in a windy environment based on the construction of an effective gust estimator. Flight tests have been conducted to verify its performance, and they demonstrate improved gust-attenuation capability in the RUAV. The proposed feedback-feedforward controller can dynamically and synchronously compensate for the gust effect. In addition, a nonlinear H1 controller has been designed for horizontal position tracking which shows rapid position tracking performance and gust-attenuation capability when gusts occur. This thesis also contains a description of technical contributions necessary for a real-time evaluation of the landing system. A high-infedlity simulation framework has been developed with the goal of minimizing the number of iterations required for theoretical analysis, simulation verification and flight validation. The real-time performance of the landing system is assessed in simulations using the C-code, which can be easily transferred to the autopilot for flight tests. All the subsystems are parameterized and can be extended to different RUAV platforms. The integration of helicopter flight dynamics, flapping dynamics, ship motion, gust effect, the flight control system and servo dynamics justifies the reliability of the simulation results. Also, practical constraints are imposed on the simulation to check the robustness of the flight control system. The feasibility of the landing procedure is confimed for the Vario helicopter using real-time ship motion data

Modification of the AdaBoost-based Detector for Partially Occluded Faces

While face detection seems a solved problem under general conditions, most state-of-the-art systems degrade rapidly when faces are partially occluded by other objects. This paper presents a solution to detect partially occluded faces by reasonably modifying the AdaBoost-based face detector. Our basic idea is that the weak classifiers in the AdaBoost-based face detector, each corresponding to a Haar-like feature, are inherently a patch-based model. Therefore, one can divide the whole face region into multiple patches, and map those weak classifiers to the patches. The weak classifiers belonging to each patch are re-formed to be a new classifier to determine if it is a valid face patch—without occlusion. Finally, we combine all of the valid face patches by assigning the patches with different weights to make the final decision whether the input subwindow is a face. The experimental results show that the proposed method is promising for the detection of occluded faces. 1