An Improved Fast Flocking Algorithm with Obstacle Avoidance for Multiagent Dynamic Systems

Author:

Wang Jialiang1ORCID,Zhao Hai1,Bi Yuanguo1,Shao Shiliang2,Liu Qian1,Chen Xingchi1,Zeng Ruofan1,Wang Yu1,Ha Le1

Affiliation:

1. College of Information Science & Engineering, Northeastern University, Shenyang 110819, China

2. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China

Abstract

Flocking behavior is a common phenomenon in nature, such as flocks of birds and groups of fish. In order to make the agents effectively avoid obstacles and fast form flocking towards the direction of destination point, this paper proposes a fast multiagent obstacle avoidance (FMOA) algorithm. FMOA is illustrated based on the status of whether the flocking has formed. If flocking has not formed, agents should avoid the obstacles toward the direction of target. If otherwise, these agents have reached the state of lattice and then these agents only need to avoid the obstacles and ignore the direction of target. The experimental results show that the proposed FMOA algorithm has better performance in terms of flocking path length. Furthermore, the proposed FMOA algorithm is applied to the formation flying of quad-rotor helicopters. Compared with other technologies to perform the localization of quad-rotor helicopter, this paper innovatively constructs a smart environment by deploying some wireless sensor network (WSN) nodes using the proposed localization algorithm. Finally, the proposed FMOA algorithm is used to conduct the formation flying of these quad-rotor helicopters in the smart environment.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Applied Mathematics

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