DocumentCode :
3722617
Title :
UAV Path Planning Based on Chaos Ant Colony Algorithm
Author :
Daqiao Zhang;Yong Xian;Jie Li;Gang Lei;Yan Chang
Author_Institution :
Xi´an Res. Inst. Of Hi-Tech Hongqing Town, Xi´an, China
fYear :
2015
Firstpage :
81
Lastpage :
85
Abstract :
Aiming at the problems that the low convergent rate and easily failing into local extremum of the ant colony algorithm (ACA) in the process of path planning, a new method based on the chaos ant colony algorithm (CACA) is proposed. By adding the chaos disturbance factor into standard ACA, the ACA defects of fall into local optimum is effectively overcome and the searching efficiency is improved. By adding target guiding factor into ACA, the direction fuzzy exists in the ant´s transfer is effectively avoided, the direction of the search is strengthened and the quality of result is improved. Through the path planning test considering the constraints of threats and turning radius, test results show that CACA can effectively avoid falling into local optimum, and get better penetration paths that meet the restraint conditions of threats and turning radius.
Keywords :
"Path planning","Chaos","Turning","Planning","Radar","Fuels","Convergence"
Publisher :
ieee
Conference_Titel :
Computer Science and Mechanical Automation (CSMA), 2015 International Conference on
Type :
conf
DOI :
10.1109/CSMA.2015.23
Filename :
7371627
Link To Document :
بازگشت