TY  - INPR
ID  - SisLab3741
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3741/
A1  - Dang, Thi Huong Giang
A1  - Vuong, Quang Huy
A1  - Ha, Minh Hoang
A1  - Pham, Minh Trien
Y1  - 2019/12//
N2  - Path planning for Unmanned Aerial Vehicle (UAV) targets at generating an optimal global path to the target, avoiding collisions and optimizing the given cost function under constraints. In this paper, the path planning problem for UAV in pre-known 3D environment is presented. Particle Swarm Optimization (PSO) was proved the efficiency for various problems. PSO has high convergence speed yet with its major drawback of premature convergence when solving large-scale optimization problems. In this paper, the improved PSO with adaptive mutation to overcome its drawback in order to applied PSO the UAV path planning in real 3D environment which composed of mountains and constraints. The effectiveness of the proposed PSO algorithm is compared to Genetic Algorithm, standard PSO and other improved PSO using 3D map of Daklak, Dakrong and Langco Beach. The results have shown the potential for applying proposed algorithm in optimizing the 3D UAV path planning.
PB  - VNU
JF  - VNU Journal of Science: Computer Science and Communication Engineering
SN  - 2588-1086
TI  - Improved Particle Swarm Optimization of Three-Dimensional Path Planning for Fixed Wing Unmanned Aerial Vehicle
AV  - public
ER  -