Automatic Pipeline Surveillance Air-Vehicle

This thesis presents the developments of a vision-based system for aerial pipeline Right-of-Way surveillance using optical/Infrared sensors mounted on Unmanned Aerial Vehicles (UAV). The aim of research is to develop a highly automated, on-board system for detecting and following the pipelines; while simultaneously detecting any third-party interference. The proposed approach of using a UAV platform could potentially reduce the cost of monitoring and surveying pipelines when compared to manned aircraft. The main contributions of this thesis are the development of the image-analysis algorithms, the overall system architecture and validation of in hardware based on scaled down Test environment. To evaluate the performance of the system, the algorithms were coded using Python programming language. A small-scale test-rig of the pipeline structure, as well as expected third-party interference, was setup to simulate the operational environment and capture/record data for the algorithm testing and validation. The pipeline endpoints are identified by transforming the 16-bits depth data of the explored environment into 3D point clouds world coordinates. Then, using the Random Sample Consensus (RANSAC) approach, the foreground and background are separated based on the transformed 3D point cloud to extract the plane that corresponds to the ground. Simultaneously, the boundaries of the explored environment are detected based on the 16-bit depth data using a canny detector. Following that, these boundaries were filtered out, after being transformed into a 3D point cloud, based on the real height of the pipeline for fast and accurate measurements using a Euclidean distance of each boundary point, relative to the plane of the ground extracted previously. The filtered boundaries were used to detect the straight lines of the object boundary (Hough lines), once transformed into 16-bit depth data, using a Hough transform method. The pipeline is verified by estimating a centre line segment, using a 3D point cloud of each pair of the Hough line segments, (transformed into 3D). Then, the corresponding linearity of the pipeline points cloud is filtered within the width of the pipeline using Euclidean distance in the foreground point cloud. Then, the segment length of the detected centre line is enhanced to match the exact pipeline segment by extending it along the filtered point cloud of the pipeline. The third-party interference is detected based on four parameters, namely: foreground depth data; pipeline depth data; pipeline endpoints location in the 3D point cloud; and Right-of-Way distance. The techniques include detection, classification, and localization algorithms. Finally, a waypoints-based navigation system was implemented for the air- vehicle to fly over the course waypoints that were generated online by a heading angle demand to follow the pipeline structure in real-time based on the online identification of the pipeline endpoints relative to a camera frame

A hardware-in-the-loop testing facility for unmanned aerial vehicle sensor suites and control algorithms

In the past decade Unmanned Aerial Vehicles (UAVs) have rapidly grown into a major field of robotics in both industry and academia. Many well established platforms have been developed, and the demand continues to grow. However, the UAVs utilized in industry are predominately remotely piloted aircraft offering very limited levels of autonomy. In contrast, fully autonomous flight has been achieved in research, and the degree of autonomy continues to grow, with research now focusing on advanced tasks such as navigating cluttered terrain and formation ying.The gap between academia and industry is the robustness of control algorithms. Academic research often focuses on proof of concept demonstrations with little or no consideration to real world concerns such as adverse weather or sensor integration.One of the goals of this thesis is to integrate real world issues into the design process. A testing environment was designed and built that allows sensors and control algorithms to be tested against real obstacles and environmental conditions in a controlled, repeatable fashion. The use of this facility is demonstrated in the implementation of a safe landing zone algorithm for a robotic helicopter equipped with a laser scanner. Results from tests conducted in the testing facility are used to analyze results from ights in the field.Controlling the testing environment also provides a baseline to evaluate different control solutions. In the current research paradigm, it is difficult to determine which research questions have been solved because the testing conditions vary from researcher to researcher. A common testing environment eliminates ambiguities and allows solutions to be characterized based on their performance in different terrains and environmental conditions.This thesis explores how flight tests can be conducted in the lab using the actual hardware and control algorithms. The sensor package is attached to a 6 DOF gantry whose motion is governed by the dynamic model of the aircraft. To provide an expansive terrain over which the flight can be conducted, a scaled model of the environment was created.The the feasibility of using a scaled environment is demonstrated with a common sensor package and control task: using computer vision to guide an autonomous helicopter. The effcts of scaling are investigated, and the approach validated by comparing results in the scaled model to actual flights. Finally, it is demonstrated how the facility can be used to investigate the effect of adverse conditions on control algorithm performance. The overarching philosophy of this work is that incorporating real world concerns into the design process leads to more fully developed and robust solutions.Ph.D., Mechanical Engineering -- Drexel University, 201

Micro Aerial Projector - stabilizing projected images of an airborne robotics projection platform

A mobile flying projector is hard to build due to the limited size and payload capability of a micro aerial vehicle. Few flying projector designs have been studied in recent research. However, to date, no practical solution has been presented. We propose a versatile laser projection system enabling in-flight projection with feedforward correction for stabilization of projected images. We present a quantitative evaluation of the accuracy of the projection stabilization in two autonomous flight experiments. While this approach is our first step towards a flying projector, we foresee interesting applications, such as providing on-site instructions in various human machine interaction scenarios

Summary of Research 1994

The views expressed in this report are those of the authors and do not reflect the official policy or position of the Department of Defense or the U.S. Government.This report contains 359 summaries of research projects which were carried out under funding of the Naval Postgraduate School Research Program. A list of recent publications is also included which consists of conference presentations and publications, books, contributions to books, published journal papers, and technical reports. The research was conducted in the areas of Aeronautics and Astronautics, Computer Science, Electrical and Computer Engineering, Mathematics, Mechanical Engineering, Meteorology, National Security Affairs, Oceanography, Operations Research, Physics, and Systems Management. This also includes research by the Command, Control and Communications (C3) Academic Group, Electronic Warfare Academic Group, Space Systems Academic Group, and the Undersea Warfare Academic Group