Current research on Unmanned Aerial Vehicles (UAVs) shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL) simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS) sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically.
This article examines and shows mathematical results of classical algorithm, which is used for small Unmanned Aerial Vehicle (UAV) navigation. The research is done with mathematical UAV model, which eliminates aerodynamics while the chosen flight path is followed by using vector field method. Lots of attention is dedicated to show possible flight path error values with representation of modelled flight path trajectories and deviations from the flight mission path. All of the modelled flight missions are done in two-dimensional space and all of the collected data with flight path error values are evaluated statistically. The most possible theoretical flight path error values are found and the general flight path error tendencies are predicted.
This paper shows mathematical results of three methods, which can be used for Unmanned Aerial Vehicle (UAV) to make transition from one flight leg to another. In paper, we present general equations, which can be used for generating waypoint-switching methods when for experiment purpose mathematical UAV model is used. UAV is modelled as moving dot, which eliminates all of the aerodynamics factors and we can concentrate only on the navigation problems. Lots of attention is dedicated to show possible flight path error values with representation of modelled flight path trajectories and deviations from the flight mission path. All of the modelled flight missions are done in two-dimensional space and all the results are evaluated by looking at Probability Density Function (PDF) values, as we are mostly interested in the probability of the error.
C priedas. Skrydžių realiomis sąlygomis navigacijos duomenų pirmas įrašas C.1 lentelė. Autonominio skrydžio naudojant autopilotą "Pixhawk 2.1" pirmojo bandymo realiomis orų sąlygomis GNSS imtuvo duomenų įrašas Table C.1. GNSS receiver data log of the first real flight experiment using "Pixhawk 2.1" autopilot system
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