Planning algorithms have applications in many fields such as robotics, logistics, and more.Planning for terrain following flights can be to utilize features of the terrain to minimizethe risk of detection. The similar problem of terrain avoidance is applicable to planningthe movement for survey or search vehicles, where low and fixed altitude may be important.Common problems that arise when planning for terrain following flights is that the dynamics ofthe vehicle are difficult to model, the state space is only represented in an approximate mannerand detailed calculations of the subject are computationally expensive. This work presents aplanning algorithm for the vertical component of terrain following flight paths using methods ofenergy, where the path itself is modelled as an elastic band deformed by virtual forces to followthe terrain. Using linear internal equations of motion for the elastic band, the computationalcomplexity can be kept low. Similar ideas have been used for planning algorithms in otherworks, but novel to the method presented here is that complicated limitations to the dynamicsof the vehicle can be treated in an effective manner. This is achieved by an adaptive linearcombination of different models for the internal elastic forces.

This project is part of research funded by NASA Langley in field of Unmanned Aerial Vehicles (UAVs) and is based on past work conducted at Virginia Commonwealth University. Dr. Mark A. Motter of NASA Langley intends to use the new autopilot system to test aircraft with many control surfaces. The goal of this project is to port an existing UAV autopilot system that has more computing power than the previous generation system to allow for more advanced flight control algorithms.The steps taken to complete this project include choosing a new hardware platform, porting C flight control software from a MicroBlaze platform to a PowerPC platform, and developing FPGA based hardware to interface with external sensors. The Suzaku-V based system was shown to have much better computing performance than the previous system, and several successful test flights have proved the viability of the new autopilot system.

This work outlines a design for a small form-factor flight control system designed to fly in a wide variety of airframes. The system was designed with future expansion in mind while providing a complete, all-in-one solution to meet present needs. This system as presented meets most needs while remaining relatively low cost. It has a completely integrated IMU solution as well as on- board GPS. It is capable of basic waypoint navigation. This solution was testing using software and hardware-in-the-loop simulation which proved its functionality.

Approved for public release; distribution is unlimited / Today, there is no way to ensure that the personnel working within the cockpit of an aircraft in flight are authorized to be there. The primary goal of this thesis is to propose a hypothetical design for the use of a nonintrusive mechanism on the flight deck of an aircraft to provide continuous or periodic authentication of authorized aircraft personnel. The mechanism should answer questions such as: "Is the person who is flying the plane actually the person who they say they are?" and "Is the correct person in control of the aircraft throughout the whole flight segment?" We will investigate biometrics as a possible security mechanism. In this thesis, various biometric methods are examined and their application in the flight deck is shown. Studies that have been conducted on real biometric devices are examined and their results are reported. Also examined are the current practices and procedures that take place in the flight deck, so that the proposed designs can be understood to not interfere with current activities therein. Two biometric solutions (i.e. proposed designs) to provide continuous or periodic authentication of authorized personnel in the flight deck are introduced. The proposed designs are general and can be used with different types of biometric device(s), and can be extended to include multi-biometrics. / Naval Postgraduate School author (civilian).

The performance of a quadrotor can be significantly disturbed in presence of wind. In this paper, a simple-to-implement attitude controller is proposed to render a robust and accurate trajectory tracking in presence of disturbance and model uncertainties. The attitude controller design is based on Quantitative Feedback Theory (QFT). A fuzzy logic controller is further employed to provide satisfactory position trajectory tracking for the quadrotor. The performances of the controllers, in terms of disturbance rejection and trajectory tracking are experimentally studied. Finally, a flight scenario is performed to compare the performances of the designed QFT-Fuzzy control scheme with the ArduCopter controller. / May 2016

Bumblebees, like other Hymenopterans, perform learning flights when departing their nest for the first few times or when departing from a newly discovered food source. As bees can learn about the landmarks around a flower both on approach and on departure, it is possible that what they see and learn on approach affects what they focus on during their learning flight on departure. In the present study, bumblebees from a commercial colony placed in a greenhouse were allowed to land at an artificial flower next to a single cylindrical landmark in one of three different positions (west, north or east), while all bees departed the flower with all three landmarks present in each position. Bumblebees approaching the flower with the landmark in the west position (WEST bees) faced mostly in a westerly direction and toward that landmark on departure, while NORTH bees faced mostly in an easterly direction and toward the east landmark and EAST bees faced mostly in a northerly direction and toward the north landmark. Thus, each group was consistent but favoured a different direction and faced toward a different landmark compared to the other groups, though these differences were most prominent during the early phase of the learning flight. On the other hand, all three groups faced the flower during the late phase of the learning flight. I therefore conclude that bumblebees do learn about the landmarks around a flower on approach, and this affects the direction they face during their learning flight in a consistent way.

Li Yiu-Ching. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (p. 123-132). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

The Centers for Disease Control and Prevention deemed the increase in overdose fatalities, due to the use of opioids, an “opioid epidemic” in the United States. Heroin, fentanyl, and other synthetic opioids are commonly abused and are contributing to the opioid epidemic. In 2016, the Drug Enforcement Administration temporarily placed three fentanyl analogs (beta-hydroxythiofentanyl, butyryl fentanyl, and furanyl fentanyl) under Schedule I due to their imminent threat to public health. These drugs elicit analgesic effects similar to heroin making them desirable drugs to abuse. Novel fentanyl analogs and designer opioids are expected to become more prominent in forensic casework in the near future as the opioid epidemic continues. These drugs can be seen in forensic seized drug and urine casework samples either alone or mixed with other drugs of abuse. It is therefore necessary to have an efficient methodology to identify these new compounds. Currently, gas chromatography-mass spectrometry (GC/MS) is used to identify drugs of abuse and is considered the “gold standard” in forensic casework. However, analysis times can often range from 15 to 60 minutes in length. Another drawback is the need for spectral library matching, which requires analytical reference materials for identification. Therefore, the identification of novel fentanyl analogs and designer drugs is limited until a reference material becomes available. In this study, direct sample analysis time-of-flight mass spectrometry (DSA-TOFMS) was evaluated to provide rapid identification of fentanyl and other synthetic opioids in seized drug and urine casework samples. DSA is a direct ambient ionization source, which requires no chromatography and minimal sample preparation. TOFMS is a high resolution mass spectrometer that uses collision-induced dissociation (CID) to produce precursor ion and characteristic fragmentation ions, which provide additional structural and molecular formula information, allowing for the identification of compounds without a reference material. The analytes explored in this study include: heroin, 6-monoacetylmorphine (6-MAM), morphine, fentanyl, norfentanyl, 4-anilino-N-phenethylpiperidine (4-ANPP), acetyl fentanyl, beta-hydroxythiofentanyl, butyryl fentanyl, furanyl fentanyl, valeryl fentanyl, AH-7921, U-47700, buprenorphine, norbuprenorphine, desomorphine, MT-45, W-15, and W-18. Direct sample analysis time-of flight mass spectrometry (DSA-TOFMS) is a novel instrumentation that could be utilized in the forensic sciences field to qualitatively identify illicit substances in casework samples. In this study, 19 compounds of interest containing heroin, fentanyl, fentanyl analogs, and other synthetic opioids were evaluated using DSA-TOFMS. DSA-TOFMS abbreviated the workload of the analysis and was utilized to provide precursor ion and characteristic fragmentation ions within an analysis time of 20 seconds. Certified reference standards were used to optimize instrumentation settings, to determine precursor ions and characteristic fragmentation ions, and to determine the limit of detection of the instrument. A carryover study determined there were no persisting ions present when entering the capillary inlet between runs. A repeatability study revealed the DSA-TOFMS repeated results within the acceptable criteria range of above 500 counts and within 10ppm error 93% (10ppm) and 83% (1ppm). Forensic seized drug casework samples were evaluated with DSA-TOFMS and qualitatively identified. Out of the 64 samples, 89% were qualitatively identified as heroin, 4% were qualitatively identified as fentanyl, 1% was qualitatively identified as heroin and fentanyl, 3% were qualitatively identified as acetyl fentanyl, and 3% were qualitatively identified as furanyl fentanyl. The casework samples containing furanyl fentanyl were considered “true unknown unknown samples,” as the Maine Health and Environmental Testing Laboratory gas chromatography-mass spectrometry library did not have a spectrum to use for the identification of these samples. Forensic urine casework samples were evaluated with DSA-TOFMS. Samples previously confirmed to contain compounds of interest were prepared using minimal sample preparation technique (filtered using 0.45 microns syringe filters and diluted (1:10) with LC/MS grade water). Analysis displayed the limitations of DSA-TOFMS as only twelve of the forty compounds of interest were present and only three of the twelve were within the acceptable criteria range. DSA-TOFMS is a fast and reliable technique with minimal sample preparation for forensic seized drug samples. However, the concentration in complex matrixes, such as urine and blood, were unable to be qualitatively identified using this sample preparation method by DSA-TOFMS.

Thesis. 1978. Ph.D.--Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND AERONAUTICS. / Vita. / Includes bibliographical references. / Ph.D.

by Chiu, Kit Chau. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 90-92). / Abstracts in English and Chinese. / ABSTRACT --- p.02 / 摘要 --- p.04 / ACKNOWLEDGEMENTS --- p.06 / TABLE OF CONTENTS --- p.07 / LIST OF FIGURES --- p.10 / LIST OF TABLES --- p.12 / Chapter 1 --- INTRODUCTION --- p.13 / Chapter 1.1 --- Application with formation flying --- p.14 / Chapter 1.2 --- Previous work --- p.16 / Chapter 1.3 --- The present work --- p.18 / Chapter 1.4 --- Thesis outline --- p.19 / Chapter 2 --- OPTIMIZATION IN DESIRED TRAJECTORY --- p.21 / Chapter 2.1 --- Problem formulation --- p.21 / Chapter 2.1.1 --- System model --- p.21 / Chapter 2.1.2 --- System constraints --- p.22 / Chapter 2.1.3 --- Cost function of the system --- p.23 / Chapter 2.2 --- Reformation as optimal control problem --- p.23 / Chapter 2.2.1 --- Polynomial form for input --- p.24 / Chapter 2.2.2 --- Problem simplification --- p.26 / Chapter 2.3 --- Numerical case studies --- p.27 / Chapter 2.3.1 --- Case study 2-1: Equal weightings in all units and directions --- p.27 / Chapter 2.3.2 --- Case study 2-2: Equal weightings in all directions but different weightings in control units --- p.30 / Chapter 2.3.3 --- Case 2-3: Different weightings in x-y-z directions but equal weightings in all control units --- p.33 / Chapter 2.4 --- Chapter summary --- p.35 / Chapter 3 --- OBSTACLE AVOIDANCE --- p.36 / Chapter 3.1 --- Additions of obstacle constraints --- p.36 / Chapter 3.2 --- Simulation case studies --- p.37 / Chapter 3.2.1 --- Case study 3-1: No obstacle --- p.38 / Chapter 3.2.2 --- Case study 3-2: Single obstacles --- p.40 / Chapter 3.2.3 --- Case study 3-3: Two obstacles --- p.42 / Chapter 3.2.4 --- Case study 3-4: Two obstacles and optimal velocity --- p.48 / Chapter 3.3 --- Chapter summary --- p.51 / Chapter 4 --- FUZZY INTERACTIVE FORCE BETWEEN ELEMENTS --- p.52 / Chapter 4.1 --- Region of repulsive force --- p.52 / Chapter 4.2 --- Region of attractive force --- p.53 / Chapter 4.3 --- Beyond the attractive region --- p.53 / Chapter 4.4 --- Interactive force as function of separation --- p.54 / Chapter 4.5 --- Fuzzy mapping --- p.55 / Chapter 4.6 --- Chapter summary --- p.58 / Chapter 5 --- VIRTUAL LEADER --- p.59 / Chapter 5.1 --- Virtual leader --- p.59 / Chapter 5.2 --- Two maneuverable elements and two virtual leaders --- p.60 / Chapter 5.3 --- Rotational Trajectories for the two virtual leaders --- p.61 / Chapter 5.4 --- Chapter summary --- p.65 / Chapter 6 --- OPIMIZATION BY INTERACTIVE FORCE --- p.66 / Chapter 6.1 --- Narrow channel passage --- p.66 / Chapter 6.2 --- Interactive forces --- p.68 / Chapter 6.3 --- Definition of interactive force --- p.69 / Chapter 6.4 --- Formulation as optimization problem --- p.71 / Chapter 6.4.1 --- Parameterization of f1 and f2 --- p.71 / Chapter 6.4.2 --- Reformulated optimization problem --- p.73 / Chapter 6.5 --- Simulation results --- p.74 / Chapter 6.6 --- Chapter summary --- p.77 / Chapter 7 --- MODIFICATION IN OBSTACLE --- p.78 / Chapter 7.1 --- Modification for interactive force --- p.78 / Chapter 7.2 --- Modification in obstacle description --- p.79 / Chapter 7.3 --- """Shortest distance"" between control unit and obstacle" --- p.80 / Chapter 7.4 --- Simulation case studies --- p.81 / Chapter 7.4.1 --- Case study 7-1: Single triangular obstacle --- p.81 / Chapter 7.4.2 --- Case study 7-2: Two triangular obstacles --- p.83 / Chapter 7.5 --- Chapter summary --- p.85 / Chapter 8 --- Conclusions and future works --- p.86 / Chapter 8.1 --- Conclusions --- p.86 / Chapter 8.2 --- Future works --- p.88 / Chapter 8.2.1 --- Fuzzy mapping --- p.88 / Chapter 8.2.2 --- Intrinsic parameters and properties --- p.89 / BIBLIOGRAPHY --- p.90