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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Autonomous visual tracking of stationary targets using small unmanned aerial vehicles

Prince, Robert A. 06 1900 (has links)
Approved for public release, distribution is unlimited / A control system was developed for autonomous visual tracking of a stationary target using a small unmanned aerial vehicle. The kinematic equations of this problem were developed, and the insight obtained from examination was applied in developing controllers for the system. This control system controlled the orientation of the camera to keep it constantly pointing at the target, and also controlled the trajectory of the aircraft in flight around the target. The initial control law that was developed drives the aircraft trajectory to a constant radius around the target. The range to the target is not directly measurable, so it was estimated using steady state Kalman filters. Once a range estimate is obtained, it is used to control the range to the target, and the aircraft trajectory is driven toward a circle with a specified radius. Initial tests of the control system with Simulink simulations have shown good performance of the control system. Further testing with hardware will be conducted, and flight tests are scheduled to be conducted in the near future. Conclusions are drawn and recommendations for further study are presented. / Ensign, United States Navy
2

Vision-Based Emergency Landing of Small Unmanned Aircraft Systems

Lusk, Parker Chase 01 November 2018 (has links)
Emergency landing is a critical safety mechanism for aerial vehicles. Commercial aircraft have triply-redundant systems that greatly increase the probability that the pilot will be able to land the aircraft at a designated airfield in the event of an emergency. In general aviation, the chances of always reaching a designated airfield are lower, but the successful pilot might use landmarks and other visual information to safely land in unprepared locations. For small unmanned aircraft systems (sUAS), triply- or even doubly-redundant systems are unlikely due to size, weight, and power constraints. Additionally, there is a growing demand for beyond visual line of sight (BVLOS) operations, where an sUAS operator would be unable to guide the vehicle safely to the ground. This thesis presents a machine vision-based approach to emergency landing for small unmanned aircraft systems. In the event of an emergency, the vehicle uses a pre-compiled database of potential landing sites to select the most accessible location to land based on vehicle health. Because it is impossible to know the current state of any ground environment, a camera is used for real-time visual feedback. Using the recently developed Recursive-RANSAC algorithm, an arbitrary number of moving ground obstacles can be visually detected and tracked. If obstacles are present in the selected ditch site, the emergency landing system chooses a new ditch site to mitigate risk. This system is called Safe2Ditch.
3

Small-Target Detection and Observation with Vision-Enabled Fixed-Wing Unmanned Aircraft Systems

Morgan, Hayden Matthew 27 May 2021 (has links)
This thesis focuses on vision-based detection and observation of small, slow-moving targets using a gimballed fixed-wing unmanned aircraft system (UAS). Generally, visual tracking algorithms are tuned to detect motion of relatively large objects in the scene with noticeably significant motion; therefore, applications such as high-altitude visual searches for human motion often ignore target motion as noise. Furthermore, after a target is identified, arbitrary maneuvers for transitioning to overhead orbits for better observation may result in temporary or permanent loss of target visibility. We present guidelines for tuning parameters of the Visual Multiple Target Tracking (Visual MTT) algorithm to enhance its detection capabilities for very small, slow-moving targets in high-resolution images. We show that the tuning approach is able to detect walking motion of a human described by 10-15 pixels from high altitudes. An algorithm is then presented for defining rotational bounds on the controllable degrees of freedom of an aircraft and gimballed camera system for maintaining visibility of a known ground target. Critical rotations associated with the fastest loss or acquisition of target visibility are also defined. The accuracy of these bounds are demonstrated in simulation and simple applications of the algorithm are described for UAS. We also present a path planning and control framework for defining and following both dynamically and visually feasibly transition trajectories from an arbitrary point to an orbit over a known target for further observation. We demonstrate the effectiveness of this framework in maintaining constant target visibility while transitioning to the intended orbit as well as in transitioning to a lower altitude orbit for more detailed visual analysis of the intended target.

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