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Created with Fabric.js 1.4.5 Unmanned Aerial Vehicle controlled by LabVIEW Self stabilizingGyroscopeAccelerometerMagnetometerPressure SensorUltrasound SensorWi-Fi(n) LabVIEW SoftwareApplication Programming interfaceRun Time EngineData AcquisitionWi-Fi(n) State Commands Battery percentagePitch degreesRoll defreesYaw degreesAltitudeAcceleration Sensor data Basler A601fc-2 Camera Resolution 656x490 Y Area 2.7 square meters Fire wire cable Start Destination X One of the most important components is the LAbVIEW software. LabVIEW allows easy communication between hardware platforms.Data can be collected and processed in real time and useful information can be conveyed to the user[1]. LabVIEW is a programming language like any other, except that the code is graphical. Its compiler directly translates the graphical code into machine code. Where the Run Time Engine executes the machine code[2]. Navigation is based on a GPS systemwhere the camera is the satelliteand the UAV is being directed.The user specifies the coordinates the UAV must move to, and the camera tracks the coordinatesof the UAV. The program figures out the shortest path to the user specified targe keeping in mind that the UAV must move in a stable manner[4]. The UAV will always face forward this helps simplify navigation with the external camera. Movement is not in one burst but in a series of pulses as to help stop the UAV and prevent it from overshooting its destination. Wi-Fi 80.11 technology has a considerable range and is capabile of transfering flight data in realtime. Wi-Fi is reliable and its responce time is acceptable. The parrot AR drone supports standardized IEEE 802.11 b,g,n Wi-Fi thus Wi-Fi(n) was the form of communication used. Wi-Fi(n) is preferred because it offers the best range, quality and stability. Remove particles Isolates a single colour in the RGB channle Unfiltered HUE filter Isolate colour This filter helps capture bright colours Filter out all small particles Role AnglePitch AngleYaw RateClimb Rate Unfiltered image straight from camera [2] Douglas Stamps, PH.D., "Learn LabVIEW 2012 Fast," in Learn LabVIEW 2012 Fast, 2013, pp. 16,17,18,19,21. [4] Nonami,K., Kendoul, F., Suzuki, S., Wang, W., & Nakazawa, D. (2010). Introduction, Autonomous Control of a Mini Quadrotor Vehicle, Mathematical Modeling and Nonlinear Control of VTOL, Vision-Based Navigation and Visual Servoing of Mini. Autonomous Flying Robots Unmanned Aurial Vehicles and Micro Aerial Vehicles (pp. 22-24, 61-75, 161-186,290-297). Tokyo: Springer Japan KK. [3] Gast, Matthew, "A survival Guide," in 802-11n, 2012, pp. 12,16,26,29,72. [1] D'Andrea, R. (n.d.). PROJECTS | Raffaello D'Andrea. RaffaelloD'Andrea | Dynamic Works. Retrieved August 2, 2013, from http://raffaello.name/dynamic-works Gratitude is extended to RGEMS for providing all the resources for this project. I would like to thank my supervisor Dr. N.Luwes and co-supervisor Mr. B.J Kotze for all of their support. Acknowlegment & References Machine vision helped bring a great deal of control and redundancy to the project. Using the camera to track a small sticker on the UAV it is possible to monitor and correct the UAV's position. In order to use the camera more effectively it was mounted almostdirectly above the UAV.
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