The purpose of this study was to compare student motivation between two junior high level computational thinking based STEM curricular activities. These two activities were a newly developed quadcopter based curriculum and a VEX based curricular activity developed for Project Lead the Way’s Gateway to Technology – Automation and Robotics course. Student motivation was assessed using an assessment called My Class Activities which broke motivation into four constructs: interest, challenge, choice, and enjoyment. This study assessed students in three schools in a northern Utah school district. Students were assessed after receiving each curriculum. Assessment responses were then coded and analyzed. The results of this study suggested that though the junior high VEX curriculum was more challenging and offered students more choice than the quadcopter curriculum, the teacher delivering the curriculum had more to do with student motivation.

Research into the improvement of the Aircraft ConceptualDesign process by the application of MultidisciplinaryOptimization (MDO) is presented. Aircraft conceptual designanalysis codes were incorporated into a variety of optimizationmethods including Orthogonal Steepest Descent (full-factorialstepping search), Monte Carlo, a mutation-based EvolutionaryAlgorithm, and three variants of the Genetic Algorithm withnumerous options. These were compared in the optimization offour notional aircraft concepts, namely an advanced multiroleexport fighter, a commercial airliner, a flying-wing UAV, and ageneral aviation twin of novel asymmetric configuration. Tobetter stress the methods, the commercial airliner design wasdeliberately modified for certain case runs to reflect a verypoor initial choice of design parameters including wingloading, sweep, and aspect ratio. MDO methods were evaluated in terms of their ability to findthe optimal aircraft, as well as total execution time,convergence history, tendencies to get caught in a localoptimum, sensitivity to the actual problem posed, and overallease of programming and operation. In all, more than a millionparametric variations of these aircraft designs were definedand analyzed in the course of this research. Following this assessment of the optimization methods, theywere used to study the issue of how the computer optimizationroutine modifies the aircraft geometric inputs to the analysismodules as the design is parametrically changed. Since thiswill ultimately drive the final result obtained, this subjectdeserves serious attention. To investigate this subject,procedures for automated redesign which are suitable foraircraft conceptual design MDO were postulated, programmed, andevaluated as to their impact on optimization results for thesample aircraft and on the realism of the computer-defined"optimum" aircraft. (These are sometimes called vehicle scalinglaws, but should not be confused with aircraft sizing, alsocalled scaling in some circles.) This study produced several key results with application toboth Aircraft Conceptual Design and MultidisciplinaryOptimization, namely:     MDO techniques truly can improve the weight and cost ofan aircraft design concept in the conceptual design phase.This is accomplished by a relatively small "tweaking" of thekey design variables, and with no additional downstreamcosts.In effect, we get a better airplane for free.     For a smaller number of variables (<6-8), adeterministic searching method (here represented by thefull-factorial Orthogonal Steepest Descent) provides aslightly better final result with about the same number ofcase evaluations     For more variables, evolutionary/genetic methods getclose to the best final result with far-fewer caseevaluations. The eight variables studied herein probablyrepresent the practical upper limit on deterministicsearching methods with today’s computer speeds.     Of the evolutionary methods studied herein, the BreederPool approach (which was devised during this research andappears to be new) seems to provide convergence in the fewestnumber ofcase evaluations, and yields results very close tothe deterministic best result. However, all of the methodsstudied produced similar results and any of them is asuitable candidate for use.     Hybrid methods, with a stochastic initial optimizationfollowed by a deterministic final "fine tuning", proved lessdesirable than anticipated.     Not a single case was observed, in over a hundred caseruns totaling over a million parametric design evaluations,of a method returning a local rather than global optimum.Even the modified commercial airliner, with poorly selectedinitial design variables far away from the global solution,was easily "fixed" by all the MDO methods studied.     The postulated set of automated redesign procedures andgeometric constraints provide a more-realistic final result,preventing attainment of an unrealistic "better" finalresult. Especially useful is a new approach defined herein,Net Design Volume, which can prevent unrealisticallyhigh design densities with relatively little setup andcomputational overhead. Further work in this area issuggested, especially in the unexplored area of automatedredesign procedures for discrete variables.

The final thesis named Tracking in Sensor Networks was created by the company Instrument control Sweden. The thesis work is to create a plug-in to an already developed software pro- gram, SkyView. Via the software program one should be able to control an IP-camera from AXIS, model 215 PTZ, with the appropriate protocol over a network.  An Application Programming Interface, API, was used to easily control the camera through SkyView. The interface is called VAPIX and is used to all cameras from AXIS. VAPIX sup- ports Hyper Text Transfer Protocol, HTTP, and Real Time Streaming Protocol, RTSP.  The video was sent through the camera with RTSP, thus an investigation resulted in that the protocol was best suited at streaming video. Steering commands to the camera was sent via HTTP. A small program was written, which was then integrated to SkyView. Features to be able to control the camera with the keyboard, mouse and a joystick were implemented. Zoom, bright- ness, focus and some more features were also added. The problem with the delay should be dealt with as soon as possible.

In this study a mechanism which produced flapping and pitching motions was designed and fabricated. These motions were produced by using a single electric motor and by exploiting flexible structures. The aerodynamic forces generated by flexible membrane wings were measured using a two degree of freedom force balance. This force balance measured the aerodynamic forces of lift and thrust. Two sets of wings with varying flexibility were made. Lift and thrust measurements were acquired as the mechanism flapped the wings in a total of thirteen cases. These thirteen cases consisted of zero velocity free stream conditions as well as forward flight conditions of five meters per second. In addition, flapping frequency was varied from two Hertz to four Hertz, while angle of attack offsets varied from zero degrees to fifteen degrees. The four most interesting conditions for both sets of wings were explored in more detail. For each of these conditions, high-speed video of the flapping wing was taken. The images from the video were also correlated with cycle averaged aerodynamic forces produced by the mechanism. Several observations were made regarding the behavior of flexible flapping wings that should aid in the design of future flexible flapping wing vehicles.

This thesis describes the development of the Texas A&M University Autonomous Helicopter System and the integration of obstacle avoidance capabilities into that system. The helicopter system, composed of a Bergen Observer helicopter and a Rotomotion Autonomous Flight Control System (AFCS), was developed as a platform to support the development of the obstacle avoidance system through integration of sensors and onboard processing capabilities. The system has proven in various flight tests that it has the capability to autonomously hover and fly to user defined GPS waypoints. The obstacle avoidance algorithm has been proven in simulations involving an interface with the Rotomotion AFCS and the flight simulation software they created to facilitate the development of that system. The helicopter has also demonstrated appropriate responses to sensor input commensurate with the obstacle avoidance algorithm. Full avoidance tests were unable to be performed due to hardware malfunctions inherent in the obstacle avoidance sensors.

<p>Research into the improvement of the Aircraft ConceptualDesign process by the application of MultidisciplinaryOptimization (MDO) is presented. Aircraft conceptual designanalysis codes were incorporated into a variety of optimizationmethods including Orthogonal Steepest Descent (full-factorialstepping search), Monte Carlo, a mutation-based EvolutionaryAlgorithm, and three variants of the Genetic Algorithm withnumerous options. These were compared in the optimization offour notional aircraft concepts, namely an advanced multiroleexport fighter, a commercial airliner, a flying-wing UAV, and ageneral aviation twin of novel asymmetric configuration. Tobetter stress the methods, the commercial airliner design wasdeliberately modified for certain case runs to reflect a verypoor initial choice of design parameters including wingloading, sweep, and aspect ratio.</p><p>MDO methods were evaluated in terms of their ability to findthe optimal aircraft, as well as total execution time,convergence history, tendencies to get caught in a localoptimum, sensitivity to the actual problem posed, and overallease of programming and operation. In all, more than a millionparametric variations of these aircraft designs were definedand analyzed in the course of this research.</p><p>Following this assessment of the optimization methods, theywere used to study the issue of how the computer optimizationroutine modifies the aircraft geometric inputs to the analysismodules as the design is parametrically changed. Since thiswill ultimately drive the final result obtained, this subjectdeserves serious attention. To investigate this subject,procedures for automated redesign which are suitable foraircraft conceptual design MDO were postulated, programmed, andevaluated as to their impact on optimization results for thesample aircraft and on the realism of the computer-defined"optimum" aircraft. (These are sometimes called vehicle scalinglaws, but should not be confused with aircraft sizing, alsocalled scaling in some circles.)</p><p>This study produced several key results with application toboth Aircraft Conceptual Design and MultidisciplinaryOptimization, namely:</p><p>    MDO techniques truly can improve the weight and cost ofan aircraft design concept in the conceptual design phase.This is accomplished by a relatively small "tweaking" of thekey design variables, and with no additional downstreamcosts.<i>In effect, we get a better airplane for free.</i></p><p>    For a smaller number of variables (<6-8), adeterministic searching method (here represented by thefull-factorial Orthogonal Steepest Descent) provides aslightly better final result with about the same number ofcase evaluations</p><p>    For more variables, evolutionary/genetic methods getclose to the best final result with far-fewer caseevaluations. The eight variables studied herein probablyrepresent the practical upper limit on deterministicsearching methods with today’s computer speeds.</p><p>    Of the evolutionary methods studied herein, the BreederPool approach (which was devised during this research andappears to be new) seems to provide convergence in the fewestnumber ofcase evaluations, and yields results very close tothe deterministic best result. However, all of the methodsstudied produced similar results and any of them is asuitable candidate for use.</p><p>    Hybrid methods, with a stochastic initial optimizationfollowed by a deterministic final "fine tuning", proved lessdesirable than anticipated.</p><p>    Not a single case was observed, in over a hundred caseruns totaling over a million parametric design evaluations,of a method returning a local rather than global optimum.Even the modified commercial airliner, with poorly selectedinitial design variables far away from the global solution,was easily "fixed" by all the MDO methods studied.</p><p>    The postulated set of automated redesign procedures andgeometric constraints provide a more-realistic final result,preventing attainment of an unrealistic "better" finalresult. Especially useful is a new approach defined herein,<i>Net Design Volume</i>, which can prevent unrealisticallyhigh design densities with relatively little setup andcomputational overhead. Further work in this area issuggested, especially in the unexplored area of automatedredesign procedures for discrete variables.</p>

Attitude estimation of unmanned aerial vehicles is of great importance as it enables propercontrol of the vehicles. Attitude estimation is typically done by an attitude-heading refer-ence system (ahrs) which utilises different kind of sensors. In this thesis these include agyroscope providing angular rates measurements which can be integrated to describe the at-titude as well as an accelerometer and a magnetometer, both of which can be compared withknown reference vectors to determine the attitude. The sensor measurements are fused usinga gps augmented 7-state Extended Kalman filter (ekf) with a quaternion and gyroscope bi-ases as state variables. It uses differentiated gps velocity measurements to estimate externalaccelerations as reference vector to the accelerometer, which significantly raises robustnessof the solution. The filter is implemented in MatlabTM and in c on an ARM microprocessor.It is compared with an explicit complementary filter solution and is evaluated with flightsusing a fixed-wing uav with satisfactory results.

Agents, by definition, (1) are situated in an environment upon which their actions affect changes and (2) have some level of autonomy from the control of humans or other agents. Being situated requires that the agent have a mechanism for sensing the environment as well as actuators for changing the environment. Autonomy implies that each agent has the freedom to make their own decisions. Rational agents are those agents that decide to execute actions that are in their “best interests” according to their desires, using a model of those desires on which they make those decisions. Action selection is complicated due to uncertainty when operating in a dynamic environment or where other actors (agents) can also influence the environment. This dissertation presents an action selection framework and algorithms that are (1) rational with respect to multiple desires and (2) responsive with respect to changing desires. Agents can use the concept of commitments, and the subsequent communication of those commitments, to coordinate their actions and reduce their uncertainty. Coordination is layered on top of this framework by describing and analyzing how commitments affect the agents’ desires in their action selection models. This research uses the domain of UAV surveillance to experimentally explore the balance between under-commitment and over-commitment. Where previous approaches concentrate on the semantics of commitment, this research concentrates on the pragmatics of commitment, describing how to use utility calculations to enable an agent to decide when making a commitment is in its best interests. / text

This work presents a novel real-time algorithm for runway detection and tracking applied to the automatic takeoff and landing of Unmanned Aerial Vehicles (UAVs). The algorithm is based on a combination of segmentation based region competition and the minimization of a specific energy function to detect and identify the runway edges from streaming video data. The resulting video-based runway position estimates are updated using a Kalman Filter, which can integrate other sensory information such as position and attitude angle estimates to allow a more robust tracking of the runway under turbulence. We illustrate the performance of the proposed lane detection and tracking scheme on various experimental UAV flights conducted by the Saudi Aerospace Research Center. Results show an accurate tracking of the runway edges during the landing phase under various lighting conditions. Also, it suggests that such positional estimates would greatly improve the positional accuracy of the UAV during takeoff and landing phases. The robustness of the proposed algorithm is further validated using Hardware in the Loop simulations with diverse takeoff and landing videos generated using a commercial flight simulator.

Systems Engineering Project Report / The Navy needs to protect Destroyers (DDGs) from Unmanned Aerial Vehicle (UAV) attacks. The team, focusing on improving the DDG’s defenses against small radar cross section UAVs making suicide attacks, established a DRM, identified current capability gaps, established a functional flow, created requirements, modeled the DDG’s current sensing and engagement capabilities in Microsoft Excel, and used Monte Carlo analysis of 500 simulation runs to determine that four out of eight incoming IED UAVs are likely to hit the ship. Sensitivity analysis showed that improving weapon systems is more effec-tive than improving sensor systems, inspiring the generation of alternatives for improving UAV defense. For the eight feasible alternatives the team estimated cost, assessed risk in accordance with the requirements, simulated performance against the eight incoming UAVs, and performed cost benefit analysis. Adding CIWS mounts is the most cost effec-tive alternative, reducing the average number of UAV hits from a baseline of 3.82 to 2.50, costing $816M to equip the 62-DDG fleet for a 12-year life cycle. Combining that with upgraded EW capabilities to jam remote-controlled UAVs reduces the hits to 1.56 for $1844M, and combining those with decoy launchers to defeat the radar-seeking Har-py UAVs reduces the hits to 1.12 for $2862M.