Work

Route Planning of UAV Based on Improved Ant Colony Algorithm

Year: 2015

Type: conference-paper

Abstract: On the basis of analyzing the tactical characteristics and the mission requirements of UAV, a route planning model is established, which is composed of a comprehensive threat model, a performance constraint model and a mission effectiveness model.A dual population genetic ant colony algorithm is designed, with which dual population ant colony can be searched and iterated independently at same time.In the iterative process, bidirectional dynamic adjust adaptively the volatile coefficient of the pheromone which is limited within a certain range.This algorithm can avoid local optimum and stagnation in the search and iteration.Finally The improved ant colony algorithm is applied to the route planning of UAV, and the feasibility and effectiveness of this method is verified by simulation.

Source: Advances in intelligent systems research/Advances in Intelligent Systems Research

DOI: 10.2991/lemcs-15.2015.283

Authors: Zhengxiang Qian, Guocheng Wang, Jingen Wang, Yongxin Shi

Institution: Institute of Applied Technology

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Natural Science Foundation of China, Natural Science Foundation of Anhui Province

Award: G241952323