Cognition-based hybrid path planning for autonomous underwater vehicle target following. (10th July 2019)

• Record Type: Journal Article
• Authors: Ming, Li Yue; Hai, Huang; Yang, Xu; Guocheng, Zhang; Jiyong, Li; Hongde, Qin
• Is Part Of: International journal of advanced robotic systems. Volume 16:Number 4(2019:Jul./Aug.)
• Publication Date: 2019-07-10
• Subjects: Autonomous underwater vehicle -- intelligent motion planning -- fuzzy rules optimization -- particle swarm optimization -- ant colony optimization; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881419857554
• Languages: English
• ISSNs: 1729-8806

Abstract

Intelligent path planning is one of the key techniques for autonomous underwater vehicles for the purpose of target detection, environmental survey and so on. In order to realize automatic motion plan, an intelligent cognitive architecture for autonomous underwater vehicle motion planning has been proposed to realize complicated target detection and mobile target following in the disturbance environment. A novel adaptive ant colony optimization and particle swarm optimization fusion-based fuzzy rules optimization algorithm has been proposed to generate optimized fuzzy rules. Through this optimization algorithm, the preliminary fuzzy rules can be optimized to realize intelligent motion planning for complicated operation tasks. Experiments of channel following for wall detection and mobile target following in the oceanic environment have verified the validity of path planning method in the implementation of detection and operation tasks.