Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor

Abstract

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.

Analysis of the Hybrid Global Path Planning Algorithm for Different Environments

“…Thus, the steady state cornering condition is accepted. The Dubins path approach, which is further applied in this work, was initially described in detail for the use of unmanned aerial vehicles obstacle avoidance in (Kikutis et al, 2017) and should be applied as follows.…”

“…Due to its convenience and significant performance, the genetic algorithm as an optimisation technique, is selected. Seeking to apply the genetic algorithm, an objective function was developed: (6) where , are the position coordinates of the centre of mass of the AGV and , , are the reference coordinates of the generated Dubins path; is the constant reference velocity of the AGV, at which it should finish the section of the optimised path; is the wheelbase of the AGV; is the distance from the centre of the mass to the rear axle of the AGV; is the reference moving time from one transition point to the next transition point; −1 is the AGV orientation at the previous transition point.…”

Path Planning and Real-Time Collision Avoidance Based on the Essential Visibility Graph

“…One of the most effective categories of path planning techniques is based on geometrical methods, which can be implemented in real time due to their low computational burden. The most famous approach is probably the one based on Dubins' car [10][11][12][13][14], in which planned paths are made up as a sequence of straight lines and circular arcs.…”

Monocular Vision-based Aircraft Ground Obstacle Classification

“…In the literature, the detection and avoidance of ground obstacles is discussed for example in [6], [7], [8], [9] and [10].…”

“…[6] Proposes a stereo vision-based obstacle avoidance scheme for ground vehicles. [7] discusses path planning to avoid obstacles with known position. [8] quadrotor helicopter and applying ground station-based calculations.…”