Autonomous obstacle avoidance for fixed-wing unmanned aerial vehicles

Author:

de Ruiter A. H. J.,Owlia S.

Abstract

AbstractThis paper investigates a method for autonomous obstacle avoidance for fixed-wing unmanned aerial vehicles (UAVs), utilising potential fluid flow theory. The obstacle avoidance algorithm needs only compute the instantaneous local potential velocity vector, which is passed to the flight control laws as a direction command. The approach is reactive, and can readily accommodate real-time changes in obstacle information. UAV manoeuvring constraints on turning or pull-up radii, are accounted for by approximating obstacles by bounding rectangles, with wedges added to their front and back to shape the resulting fluid pathlines. It is shown that the resulting potential flow velocity field is completely determined by the obstacle field geometry, allowing one to determine a non-dimensional relationship between obstacle added wedge-length and the corresponding minimum pathline radius of curvature, which can then be readily scaled in on-board implementation. The efficacy of the proposed approach has been demonstrated numerically with an Aerosonde UAV model.

Publisher

Cambridge University Press (CUP)

Subject

Aerospace Engineering

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. On the Problem of UAV Collision Avoidance based on Adaptive Load Factor Control;2022 International Conference on Unmanned Aircraft Systems (ICUAS);2022-06-21

2. Research into Collision Avoidance Models for Unmanned Aerial Vehicles;2022 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM);2022-05-16

3. Implementation of Quadrotor Path Planning Using Fluid Flow Equations;2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET);2021-12-08

4. Deep Reinforcement Learning for Quadrotor Path Following and Obstacle Avoidance;Deep Learning for Unmanned Systems;2021

5. Real-Time Autonomous Obstacle Avoidance for Fixed-Wing UAVs Using a Dynamic Model;Journal of Aerospace Engineering;2020-07

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