UAV Path Planning Based on Chaos Ant Colony Algorithm

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.