A biologically inspired neural network for navigation with obstacle avoidance in autonomous underwater and surface vehicles

Author

Guerrero-González, Antonio ; García-Córdova, Francisco ; Gilabert, Javier

Author_Institution

(UVL-UPCT) Underwater Vehicles Lab., Tech. Univ. of Cartagena (UPCT), Cartagena, Spain

fYear

2011

fDate

6-9 June 2011

Firstpage

1

Lastpage

8

Abstract

This paper describes a neural network model for the reactive behavioural navigation of an autonomous underwater vehicle (AUV) in which an innovative, neurobiological inspired sensorization control system and a hardware architectures are being implemented. The AUV has been with several types of environmental and oceanographic instruments such as CTD sensors, chlorophyll, turbidity, optical dissolved oxygen (YSI V6600 sonde) and nitrate analyzer (SUNA) together with ADCP, side scan sonar and video camera, in a flexible configuration to provide a water quality monitoring platform with mapping capabilities. This neurobiological inspired control architecture for autonomous intelligent navigation was implemented on an AUV capable of operating during large periods of time for observation and monitoring. In this work, the autonomy of the AUV is evaluated in several scenarios.

Keywords

collision avoidance; neurocontrollers; remotely operated vehicles; sensors; underwater vehicles; CTD sensors; YSI V6600 sonde; autonomous intelligent navigation; autonomous underwater robots; autonomous underwater vehicles; biologically inspired neural network; environmental instruments; hardware architectures; mapping capabilities; neurobiological inspired sensorization control system; nitrate analyzer; obstacle avoidance; oceanographic instruments; optical dissolved oxygen; reactive behavioural navigation; side scan sonar; surface vehicles; video camera; water quality monitoring platform; Angular velocity; Context; Navigation; Propellers; Robot sensing systems; Vehicles; Autonomous under vehicle (AUV); learning control adaptive behaviour; neural networks; obstacle avoidance; robot navigation;

fLanguage

English

Publisher

ieee

Conference_Titel

OCEANS, 2011 IEEE - Spain

Conference_Location

Santander

Print_ISBN

978-1-4577-0086-6

Type

conf

DOI

10.1109/Oceans-Spain.2011.6003432

Filename

6003432