TY - GEN
T1 - The comparison of four UAV path planning algorithms based on geometry search algorithm
AU - He, Ze Fang
AU - Zhao, Long
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/20
Y1 - 2017/9/20
N2 - The comparative study of four practical three-dimensional (3D) path planning algorithm based on geometry search is proceeded in this paper, the four algorithms include Dijkstra algorithm, Floyd algorithm, A∗ algorithm and Ant colony algorithm. In four algorithms, the working environments of Unmanned Aerial Vehicle (UAV) are all modeled using grid map method and UAV three-dimensional paths are all obtained by amending two-dimensional paths with the terrain following algorithm. In addition, a perpendicular approach is used to choose the key path node during UAV path planning. In this paper, online real-Time path planning abilities of the four algorithms are compared from the two aspects of the run time and the path length. Simulation results show that the four algorithms can all handle fixed threats and sudden threats, and their planning time are short; but synthetically considering the run time, complexity and path length of the four algorithms, Dijkstra algorithm is in turn better than Floyd algorithm, A∗ algorithm and Ant colony algorithm.
AB - The comparative study of four practical three-dimensional (3D) path planning algorithm based on geometry search is proceeded in this paper, the four algorithms include Dijkstra algorithm, Floyd algorithm, A∗ algorithm and Ant colony algorithm. In four algorithms, the working environments of Unmanned Aerial Vehicle (UAV) are all modeled using grid map method and UAV three-dimensional paths are all obtained by amending two-dimensional paths with the terrain following algorithm. In addition, a perpendicular approach is used to choose the key path node during UAV path planning. In this paper, online real-Time path planning abilities of the four algorithms are compared from the two aspects of the run time and the path length. Simulation results show that the four algorithms can all handle fixed threats and sudden threats, and their planning time are short; but synthetically considering the run time, complexity and path length of the four algorithms, Dijkstra algorithm is in turn better than Floyd algorithm, A∗ algorithm and Ant colony algorithm.
KW - A
KW - Algorithm
KW - Ant colony algorithm
KW - Dijkstra algorithm
KW - Floyd algorithm
KW - Path planning
KW - UAV
UR - https://www.scopus.com/pages/publications/85034429702
U2 - 10.1109/IHMSC.2017.123
DO - 10.1109/IHMSC.2017.123
M3 - 会议稿件
AN - SCOPUS:85034429702
T3 - Proceedings - 9th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2017
SP - 33
EP - 36
BT - Proceedings - 9th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2017
Y2 - 26 August 2017 through 27 August 2017
ER -