Litcius/Paper detail

A Novel Algorithm of Multi-AUVs Task Assignment and Path Planning Based on Biologically Inspired Neural Network Map

Daqi Zhu, Bei Zhou, Simon X. Yang

2020IEEE Transactions on Intelligent Vehicles104 citationsDOI

Abstract

The task assignment and path planning of a multi-AUVs system has now attracted considerable attention and become a hotspot in the research. In this paper, a novel algorithm of multi-AUVs task assignment and path planning based on Biologically Inspired Neural Network Map (BINN) is proposed. Firstly, the grid map is built by discretizing the three-dimensional underwater environment into many equal grids. Secondly, the activity values of all AUVs in the BINN maps of each target are calculated. Then, the AUV with the highest activity value in the BINN map of the target is selected as the winning AUV for the target. Finally, the winning AUV performs path planning according to the BINN strategy. Through the simulation experiment, it is proved that the novel BINN algorithm proposed in this paper can effectively and reasonably distribute multi-AUVs and reduce the overall sailing distance.

Topics & Concepts

Motion planningUnderwaterGrid referenceGridComputer scienceArtificial neural networkTask (project management)Path (computing)AlgorithmDiscretizationArtificial intelligenceReal-time computingEngineeringGeographyMathematicsMobile robotGeodesyMathematical analysisArchaeologySystems engineeringProgramming languageRobotUnderwater Vehicles and Communication SystemsRobotic Path Planning AlgorithmsRobotics and Sensor-Based Localization