A Fast Global Flight Path Planning Algorithm Based on Space Circumscription and Sparse Visibility Graph for Unmanned Aerial Vehicle

Abdul Majeed,Sungchang Lee

doi:10.3390/electronics7120375

Abstract

This paper proposes a new flight path planning algorithm that finds collision-free, optimal/near-optimal and flyable paths for unmanned aerial vehicles (UAVs) in three-dimensional (3D) environments with fixed obstacles. The proposed algorithm significantly reduces pathfinding computing time without significantly degrading path lengths by using space circumscription and a sparse visibility graph in the pathfinding process. We devise a novel method by exploiting the information about obstacle geometry to circumscribe the search space in the form of a half cylinder from which a working path for UAV can be computed without sacrificing the guarantees on near-optimality and speed. Furthermore, we generate a sparse visibility graph from the circumscribed space and find the initial path, which is subsequently optimized. The proposed algorithm effectively resolves the efficiency and optimality trade-off by searching the path only from the high priority circumscribed space of a map. The simulation results obtained from various maps, and comparison with the existing methods show the effectiveness of the proposed algorithm and verify the aforementioned claims.

Highlights

Unmanned Aerial Vehicles (UAVs) are becoming increasingly popular due to their ability to operate autonomously even in those areas that are difficult to reach, such as mountains, deserts, and forests for performing a variety of tasks
In the proposed algorithm simulations, we consider a 25-kg fixed wing unmanned aerial vehicles (UAVs) similar to our previous work [85]. We considered both local and global constraints during the simulations
We proposed a global flight path planning algorithm based on space circumscription and sparse visibility graph for unmanned aerial vehicles (UAVs) in three-dimensional (3D)

Summary

Introduction

Unmanned Aerial Vehicles (UAVs) are becoming increasingly popular due to their ability to operate autonomously even in those areas that are difficult to reach, such as mountains, deserts, and forests for performing a variety of tasks. According to the Teal Group’s forecast of the rapidly growing global UAV market, annual spending on UAVs including both military and civilian applications, will be more than US $12 billion by 2024 [1]. Technological developments, such as processing speed of computers, sensors, artificial intelligence, and computer vision based algorithms have enabled UAVs to conduct a much wider range of practical applications with ease that otherwise would be done at higher costs and times. There are plenty of methods in the existing literature to represent the UAV operating environment. A detailed survey regarding environment modelling techniques was given by

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Conclusion