UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
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Item TOWARDS AUTONOMOUS VERTICAL LANDING ON SHIP-DECKS USING COMPUTER VISION(2022) Shastry, Abhishek; Datta, Anubhav; Chopra, Inderjit; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The objective of this dissertation is to develop and demonstrate autonomous ship-board landing with computer vision. The problem is hard primarily due to the unpredictable stochastic nature of deck motion. The work involves a fundamental understanding of how vision works, what are needed to implement it, how it interacts with aircraft controls, the necessary and sufficient hardware, and software, how it differs from human vision, its limits, and finally the avenues of growth in the context of aircraft landing. The ship-deck motion dataset is provided by the U.S. Navy. This data is analyzed to gain fundamental understanding and is then used to replicate stochastic deck motion in a laboratory setting on a six degrees of freedom motion platform, also called Stewart platform. The method uses a shaping filter derived from the dataset to excite the platform. An autonomous quadrotor UAV aircraft is designed and fabricated for experimental testing of vision-based landing methods. The entire structure, avionics architecture, and flight controls for the aircraft are completely developed in-house. This provides the flexibility and fundamental understanding needed for this research. A fiducial-based vision system is first designed for detection and tracking of ship-deck. This is then utilized to design a tracking controller with the best possible bandwidth to track the deck with minimum error. Systematic experiments are conducted with static, sinusoidal, and stochastic motions to quantify the tracking performance. A feature-based vision system is designed next. Simple experiments are used to quantitatively and qualitatively evaluate the superior robustness of feature-based vision under various degraded visual conditions. This includes: (1) partial occlusion, (2) illumination variation, (3) glare, and (4) water distortion. The weight and power penalty for using feature-based vision are also determined. The results show that it is possible to autonomously land on ship-deck using computer vision alone. An autonomous aircraft can be constructed with only an IMU and a Visual Odometry software running on stereo camera. The aircraft then only needs a monocular, global shutter, high frame rate camera as an extra sensor to detect ship-deck and estimate its relative position. The relative velocity however needs to be derived using Kalman filter on the position signal. For the filter, knowledge of disturbance/motion spectrum is not needed, but a white noise disturbance model is sufficient. For control, a minimum bandwidth of 0.15 Hz is required. For vision, a fiducial is not needed. A feature-rich landing area is all that is required. The limits of the algorithm are set by occlusion(80\% tolerable), illumination (20,000 lux-0.01 lux), angle of landing (up to 45 degrees), 2D nature of features, and motion blur. Future research should extend the capability to 3D features and use of event-based cameras. Feature-based vision is more versatile and human-like than fiducial-based, but at the cost of 20 times higher computing power which is increasingly possible with modern processors. The goal is not an imitation of nature but derive inspiration from it and overcome its limitations. The feature-based landing opens a window towards emulating the best of human training and cognition, without its burden of latency, fatigue, and divided attention.Item EXPERIMENTAL INVESTIGATION OF A QUAD-ROTOR BIPLANE MICRO AIR VEHICLE(2015) Bogdanowicz, Christopher Michael; Chopra, Inderjit; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Micro air vehicles are expected to perform demanding missions requiring efficient operation in both hover and forward flight. This thesis discusses the development of a hybrid air vehicle which seamlessly combines both flight capabilities: hover and high-speed forward flight. It is the quad-rotor biplane, which weighs 240 grams and consists of four propellers with wings arranged in a biplane configuration. The performance of the vehicle system was investigated in conditions representative of flight through a series of wind tunnel experiments. These studies provided an understanding of propeller-wing interaction effects and system trim analysis. This showed that the maximum speed of 11 m/s and a cruise speed of 4 m/s were achievable and that the cruise power is approximately one-third of the hover power. Free flight testing of the vehicle successfully highlighted its ability to achieve equilibrium transition flight. Key design parameters were experimentally investigated to understand their effect on overall performance. It was found that a trade-off between efficiency and compactness affects the final choice of the design. Design improvements have allowed for decreases in vehicle weight and ground footprint, while increasing structural soundness. Numerous vehicle designs, models, and flight tests have proven system scalability as well as versatility, including an upscaled model to be utilized in an extensive commercial package delivery system. Overall, the quad-rotor biplane is proven to be an efficient and effective multi-role vehicle.Item Design and Implementation of a Control System for a Quadrotor MAV(2012) Bawek, Dean; Chopra, Inderjit; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The quadrotor is a 200 g MAV with rapid-prototyped rotors that are driven by four brushless electric motors, capable of a collective thrust of around 400 g using an 11 V battery. The vehicle is compact with its largest dimension at 188 mm. Without any feedback control, the quadrotor is unstable. For flight stability, the vehicle incorporates a linear quadratic regulator to augment its dynamics for hover. The quadrotor's nonlinear dynamics are linearized about hover in order to be used in controller formulation. Feedback comes both directly from sensors and a Luenberger observer that computes the rotor velocities. A Simulink simulation uses hardware and software properties to serve as an environment for controller gain tuning prior to flight testing. The results from the simulation generate stabilizing control gains for the on-board attitude controller and for an off-board PC autopilot that uses the Vicon computer vision system for position feedback. Through the combined effort of the on-board and off-board controllers, the quadrotor successfully demonstrates stable hover in both nominal and disturbed conditions.