DocumentCode :
2633860
Title :
Autonomous Surface Vehicle Docking Manoeuvre with Visual Information
Author :
Martins, Alfredo ; Almeida, J.M. ; Ferreira, H. ; Silva, H. ; Dias, N. ; Dias, A. ; Almeida, C. ; Silva, E.P.
Author_Institution :
Autonomous Syst. Lab., Instituto Superior de Engenharia do Porto
fYear :
2007
fDate :
10-14 April 2007
Firstpage :
4994
Lastpage :
4999
Abstract :
This work presents a hybrid coordinated manoeuvre for docking an autonomous surface vehicle with an autonomous underwater vehicle. The control manoeuvre uses visual information to estimate the AUV relative position and attitude in relation to the ASV and steers the ASV in order to dock with the AUV. The AUV is assumed to be at surface with only a small fraction of its volume visible. The system implemented in the autonomous surface vehicle ROAZ, developed by LSA-ISEP to perform missions in river environment, test autonomous AUV docking capabilities and multiple AUV/ASV coordinated missions is presented. Information from a low cost embedded robotics vision system (LSAVision), along with inertial navigation sensors is fused in an extended Kalman filter and used to determine AUV relative position and orientation to the surface vehicle The real time vision processing system is described and results are presented in operational scenario.
Keywords :
Kalman filters; attitude control; mobile robots; motion control; position control; remotely operated vehicles; robot vision; underwater vehicles; AUV attitude estimation; AUV relative position estimation; LSA-ISEP; LSAVision; ROAZ; autonomous surface vehicle docking manoeuvre; autonomous underwater vehicle; extended Kalman filter; inertial navigation sensors; robotics vision system; Attitude control; Costs; Machine vision; Marine vehicles; Mobile robots; Performance evaluation; Remotely operated vehicles; Rivers; System testing; Underwater vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2007 IEEE International Conference on
Conference_Location :
Roma
ISSN :
1050-4729
Print_ISBN :
1-4244-0601-3
Electronic_ISBN :
1050-4729
Type :
conf
DOI :
10.1109/ROBOT.2007.364249
Filename :
4209867
Link To Document :
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