Paper Info
Title
Three-Dimensional Unmanned Aerial Vehicle Route Planning Using Hybrid Differential Evolution
Abstract
Unmanned aerial vehicles (UAVs) have been investigated proactively owing to their promising applications. A route planner is key to UAV autonomous task execution. Herein, a hybrid differential evolution (HDE) algorithm is proposed to generate a high-quality and feasible route for fixed-wing UAVs in complex three-dimensional environments. A multiobjective function is designed, and both the route length and risk are optimized. Multiple constraints based on actual situations are considered, including UAV mobility, terrain, forbidden flying areas, and interference area constraints. Inspired by the wolf pack search algorithm, the proposed HDE algorithm combines differential evolution (DE) with an approaching strategy to improve the search capability. Moreover, considering the dynamic properties of fixed-wing UAVs, the quadratic B-spline curve is used for route smoothing. The HDE algorithm is compared with a state-of-the-art UAV route planning algorithm, i.e., the modified wolf pack search algorithm, and the traditional DE algorithm. Several numerical experiments are performed, and the performance comparison of algorithms shows that the HDE algorithm demonstrates better performances in terms of solution quality and constraint-handling ability in complex three-dimensional environments.
Year
DOI
Venue
2020
10.20965/jaciii.2020.p0820
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS
Keywords
DocType
Volume
unmanned aerial vehicle, route planning, differential evolution, route smoothing
Journal
24
Issue
ISSN
Citations 
7
1343-0130
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Hao Zhang19715.19
Dou Lihua214513.33
Chunxiao Cai300.34
Bin Xin426524.77